2013 Subject Index: Data and Information Technology

• Hot-Spot Identification: Categorical Binary Model Approach
  Abstract: This paper presents an alternative methodology for hot-spot identification based on a probabilistic model. In this methodology, the ranking criterion for hot-spot identification conveys the probability of a site being a hot-spot or a non-hot spot. A binary choice model was used to link the outcome to a set of factors that characterize the risk of the sites under analysis based on our use of two categories (0/1) for the dependent variable. The proposed methodology consists of two main steps. First, a threshold value for the number of accidents is set to distinguish hot spots from safe sites (category 1 or 0, respectively). Based on this classification, a binary model is applied that allows the construction of an ordered site list using the probability of a site being a hot-spot. The second step involves the choice of a selection strategy. The selection strategy can target a fixed number of sites with the greatest probability or, alternatively, all sites exceeding a specific probability, such as 0.5. A demonstration of the proposed methodology is provided using simulated data. For the simulation design, urban intersection data from Porto, Portugal, covering a five-year period were used. The results of the binary model showed a good fit. To evaluate and compare the probabilistic method with other commonly used methods, measures were used to test the performance of each method in terms of its power to detect the “true” hot spots. The test results indicate that the proposed method is superior to two commonly used methods. The gains of using this method are related to the simplicity of its application, while critical issues such as prior distribution effect assumptions and the regression-to-the-mean phenomenon are overcome. Further, the proposed model provides a realistic and intuitive perspective and supports easy practical application.
  Authors: Ferreira, Sara Pinho; Couto, António Fidalgo
  Authors: Ferreira, Sara Pinho; Couto, António Fidalgo
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-0095
• Systems Thinking for Knowledge Transfer in Organic and Mechanistic Organizations: State Government Transportation Research Organizations
  Abstract: State government transportation agency research units exist within traditionally hierarchical or mechanistic organizations. They manage and conduct research studies and ensure the successful transfer of knowledge through both inter-organizational and intra-organizational relationships, and knowledge transfer activities. These activities may entail the transfer of knowledge at the local, state, federal or international level. Improving knowledge transfer will ultimately improve organizational performance. Use of Burns and Stalkers’ dualism: “mechanistic” and “organic” management systems, to describe government organizations, will aid in recognizing the current condition, and identify the characteristics of an environment that will be more conducive to efficient knowledge transfer. This information will help decision makers within these organizations to select the appropriate organizational structure, or processes, to enhance knowledge transfer. Increasing amounts of information and growing organizational complexity require a “systems thinking” approach to identifying opportunities for improvement within these organizations. This paper describes how systems thinking can aid in exploring knowledge transfer within organic and mechanistic state government organizations. It offers contributions to the body of knowledge concerning government entities and intentional knowledge transfer.
  Authors: Crichton-Sumners, Camille
  Authors: Crichton-Sumners, Camille
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology; Education and Training
  Session: 681
  Paper Number: 13-0063
• Effects of Public Rest Areas on Fatigue-Related Crashes
  Abstract: Fatigue-related crashes account for 2.2 to 2.6 percent of all fatal crashes in the United States on an annual basis. These types of crashes are prevalent in rural areas and often result in severe injuries to crash-involved occupants. Public roadside rest areas were developed largely to alleviate motorist fatigue and reduce the opportunity for fatigue-related crashes by providing safe parking areas for tired drivers. However, research as to the safety effects of rest areas has been limited. This paper presents the results of a spatial analysis to investigate the effects of a road segment’s proximity to a rest area on the frequency of fatigue-related crashes. Poisson and negative binomial models are estimated for freeways and two-lane highways in order to isolate the effects of proximity while control for other relevant factors, such as traffic volumes. The results of these models indicate that the proximity of a road segment to the nearest rest area significantly influences crash frequencies on both types of facilities. Traffic volumes tended to have similar effects on both facility types while the effects of proximity were slightly more pronounced on two-lane highways. The study results suggest that roadside rest areas provide a safety benefit and the crash prediction models developed as a part of this research provide a simple, practical tool for use by road agencies in quantifying these impacts.
  Authors: McArthur, Adam; Savolainen, Peter Tarmo; Gates, Timothy J.
  Authors: McArthur, Adam; Savolainen, Peter Tarmo; Gates, Timothy J.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 433
  Paper Number: 13-0162
• Open Transit Data: State of the Practice and Experience from Participating Agencies in the United States
  Abstract: The availability of web and mobile applications and dynamic displays for transit traveler information has proliferated in the past few years with many new and emerging uses for transit data. Transit data about routes, stops and schedules in a machine-readable format is “open” when it is published and freely available to the public. The purpose of this study is to provide a state of the practice for open transit data: how web applications use open transit data, what benefits agencies gain by giving software developers access to the data and what the best practices are for agencies considering opening data they already have. This project is limited to static data and does not address privacy and legal issues surrounding real-time GPS location data. The research draws upon a literature review, interviews with industry experts and practitioners and primary experience coordinating a regional open transit data initiative in Atlanta, Georgia. Case study interviews conducted with five transit agencies about their experiences with open data revealed best practices and trends in customer benefits. Several key findings emerged from these agency interviews: (1) transit agencies of any size can pursue open data; (2) legal concerns about brand usage and liability can be overcome; (3) agencies should support the software development community; and (4) open data is an opportunity for positive marketing of an agency. These findings enable public agencies nationwide to embark on an open data initiative to deliver benefits for existing and potential riders at low deployment costs.
  Authors: Wong, James Christopher; Reed, Landon T; Watkins, Kari Edison; Hammond, Regan
  Authors: Wong, James Christopher; Reed, Landon T; Watkins, Kari Edison; Hammond, Regan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 283
  Paper Number: 13-0186
• Detailed Analysis of Travel Time Reliability Performance Measures from Empirical Data
  Abstract: Research on measuring travel time reliability has increased heavily in recent years. A host of measures have been proposed and researched as well as adopted by management agencies. For this study, 13 reliability measures are calculated for 983 freeway segments from 15 minute space mean speed data. Statistical tests are performed to determine how consistently the measures rank the segments at different times of day and how well correlated the measures are to the average. Analysis of the change in measures over the day as well as each measure’s relationship with the average is discussed. Temporal sampling by time of day has a large effect on the travel time reliability measures calculated. This means effects like directional demand peaks can affect direct comparisons across segment types. Ideal comparisons of reliability measures should include all 24 hours of the day, and time of day analysis can identify time periods where management strategies can have the most effect on reliability.No single measure was identified as ideal, though the semi-standard deviation performed well on most tests. It also reports values in reference to the free flow travel time, eliminating the false negative issue where the standard deviation may be very low while the average travel time is high. It is recommended that full distributions be compared where appropriate. With increasing exposure to these distributions and careful explanations as to what they represent, decision makers can effectively prioritize traffic management and geometric improvements.
  Authors: Chase, R. Thomas; Williams, Billy M.; Rouphail, Nagui M.
  Authors: Chase, R. Thomas; Williams, Billy M.; Rouphail, Nagui M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-0226
• Evolution of Modal Captivity and Mode Choice Patterns for Commuting Trips: Longitudinal Analysis by Using Cross-Sectional Data Sets
  Abstract: This paper presents an econometric model that uses multiple repeated cross-sectional datasets to explain temporal evolutions of commuting mode choice preference structures. The model explicitly addresses latent captivity to different modes in addition to systematic elements of choice behaviour. The empirical model is a pooled model and is estimated by pooling three household travel survey datasets together that are collected in the Greater Toronto and Hamilton Area (GTHA) over a 10 year time period. The empirical model clearly explains that there have been significant changes in latent captivity and the mode choice preference structure of commuting mode choice in the GTHA. Changes have occurred in the unexplained component of latent captivity to different modes; in the transportation cost perceptions among different occupation groups, and in the scales of commuting mode choice preferences. Furthermore, the pooled model developed in this paper demonstrates that pooling multiple repeated cross-sectional datasets is a more efficient method of capturing behavioural changes than using a cross-sectional model. Finally, the pooled model reveals that unexplained components of the modal captivities change more over time than the unexplained portions of the systematic utility functions. These findings highlight the necessity of considering latent captivity in commuting mode choice models for proper policy evaluations and forecasting.
  Authors: Weiss, Adam; Nurul Habib, Khandker M.
  Authors: Weiss, Adam; Nurul Habib, Khandker M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0220
• Investigating the Transferability of Individual Trip Rates: Decision Tree Approach
  Abstract: Transferring trip rates to areas without local survey data is a common practice which is typically performed in an ad-hoc fashion using household-based cross-classification tables. This paper applies a rule-based method called decision tree to develop individual-level trip generation models for eight different trip purposes as defined in the National Household Travel Survey data (NHTS 2009) in addition to their daily vehicle miles traveled (VMT). For each trip purpose, the models are then obtained by finding the best-fitted statistical distribution to each one of the final decision tree clusters while considering the correlation between different trip purposes. The rule-based models utilize several socio-demographic and land-use explanatory variables and are sensitive to changes in demographics. The performance of the models are then tested and validated in a transferability application to Phoenix Metropolitan Region. These models can be employed in a disaggregate microsimulation framework to generate trips with different purposes at individual or household level. They can also be used as an alternative solution for trip generation step of a conventional four step travel demand model.
  Authors: Fasihozaman Langerudi, Mehran; Hossein Rashidi, Taha; Mohammadian, Abolfazl
  Authors: Fasihozaman Langerudi, Mehran; Hossein Rashidi, Taha; Mohammadian, Abolfazl
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0218
• Prediction of Individual Travel Mode Using Evidential Neural Network Model
  Abstract: We apply a machine learning methods for predicting individual travel mode. This method can be used to support management decision-making and build predictions under uncertainty related to changes in people’s behavior, economic context or environment and policy. The presented method uses individuals’ characteristics, transport mode specifications and data related to places of work and residence. The dataset analyzed comes from a survey. It contains information on the daily mobility (e.g., from home to work) of individuals who either live or work in Luxembourg. We extracted individual characteristics to relate daily mobility (journeys between home and work, in particular) to the characteristics of working individuals. We used the information about public transportation specification and some geographical particularities of the residential and work places. We compared by cross-validation the rates of successful prediction obtained by ANN and several alternative approaches (Bayes, DT, ENN, k-NN, MNL, and SVM) for the travel mode. The results show that the ANN is superior to the studied alternatives. All computations and graphics have been obtained using R programming language.
  Authors: Omrani, Hichem; Charif, Omar; Awasthi, Anjali; Gerber, Philippe
  Authors: Omrani, Hichem; Charif, Omar; Awasthi, Anjali; Gerber, Philippe
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 482
  Paper Number: 13-0284
• Contrasting Artificial Intelligence Effectiveness: Application to Traffic Signal Optimization
  Abstract: Signal timing optimization in urban transportation networks is a NP-hard problem with no exact method to find an optimal solution. Therefore, researchers have used different methods and artificial intelligence algorithms to find near-optimal solutions. Choosing the right algorithm to solve the problem is extremely important since it directly influences the solution and consequently network performance. Of course, different algorithms have different convergence properties and due to the extremely large solution space of the problem, selecting a more efficient algorithm with lower runtime is vital. This study compares the performance of five meta-heuristic algorithms in optimizing traffic signals in terms of their runtimes and solution quality. These algorithms are: simple genetic algorithm (SGA), elitist genetic algorithm (EGA), micro-elitist genetic algorithm (MEGA), evolution strategy (ES) and, elitist evolution strategy (ES+).Findings indicated that when calibrated, each algorithm is capable of finding near-optimal solutions that prevent queue spillovers and gridlocks. In general, ES+ required the fewest number of Fitness Function Evaluations (FFE) to reach most levels of the upper-bound. ES required similar number of FFE to reach up to 90% of the upper-bound; however, for higher levels it was considerably slower than ES+. MEGA was very quick in early improvements in the fitness value; however, in most of the cases ES+ outperformed it reaching higher levels of the upper-bound. In symmetric demand patterns, EGA was much faster than ES+ in reaching to 97.5% of the theoretical upper-bound. Finally, SGA was in general among the least efficient algorithms for all demand patterns.
  Authors: Hajbabaie, Ali; Benekohal, Rahim F.
  Authors: Hajbabaie, Ali; Benekohal, Rahim F.
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-0264
• Establishing Automated Regional Nonmotorized Transportation Data Collection System to Support Active Transportation Performance Monitoring
  Abstract: This paper describes an effort underway in San Diego to establish a regional non-motorized data collection system in support of long-range planning for bicycle and pedestrian systems. Planners, engineers, and advocates increasingly recognize the need for accurate counts to inform investments in pedestrian and bicycle facilities (FHWA, 2011). There are currently gaps in the literature about methods for determining where non-motorized counting should occur, over what time periods, and how to use automated counts to develop adjustment factors. This paper describes one region’s efforts to link performance monitoring to regional transportation planning by establishing a network of automated bicycle and pedestrian count stations along the regional bicycle network, which was recently adopted in the 2050 Regional Transportation Plan. The count station siting methodology employed a multi-step process where the regional bicycle network was segmented, and then stratified sampling employed to select a subset of bicycle network segments where counters would be installed. The siting methodology first established a comprehensive network of count stations representing ultimate coverage of the regional bicycle network (170 count stations). Then a subset of representative locations was selected for phase one count program implementation (35 counts stations). To date, count equipment has been installed at 17 locations and the remainder will be installed by September 2012. When fully implemented, this counting program will be one of the most comprehensive automated data collection systems of any in the nation. The paper focuses on siting methodologies, validation of automated counts, and using counts for non-motorized performance monitoring.
  Authors: Ryan, Sherry
  Authors: Ryan, Sherry
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists
  Session: 425
  Paper Number: 13-0351
• Application of Stochastic Gradient Boosting Technique to Enhance Reliability of Real-Time Risk Assessment Using Automatic Vehicle Identification and Remote Traffic Microwave Sensor Data
  Abstract: This study proposes a recent promising machine learning technique to enhance the reliability of real-time risk assessment on freeways. Stochastic Gradient Boosting (SGB) is utilized to identify hazardous conditions based on traffic data collected from multiple detection systems; automatic vehicle identification (AVI) and remote traffic microwave sensors (RTMS), real-time weather stations and roadway geometry. SGB’s key strengths lie in its capability to fit complex nonlinear relationships, handling different types of predictors and accommodating missing values with no need for prior transformation of the predictor variables or elimination of outliers, which is the case of real-time applications. Boosting multiple simple trees together overcomes the drawback of single tree models of poor prediction accuracy and provides fast and superior predictive performance. In this paper, three models were calibrated; full model that is augmenting all available data and another two models to explicitly compare between the prediction performance of traffic data that are collected from different sources (AVI and RTMS) at the same location. The results from the preliminary analysis as well as the calibrated models indicate that crash prediction from AVI is comparably equivalent to RTMS data. Moreover, the full model achieved superior classification accuracy identifying about 89% of crash cases in the validation dataset with only 6.5% false positive rate. Because of the superior classification performance of SGB and its minimal required data preparation, SGB is recommended as a promising technique for real-time risk assessment application.
  Authors: Ahmed, Mohamed M.; Abdel-Aty, Mohamed A.
  Authors: Ahmed, Mohamed M.; Abdel-Aty, Mohamed A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-0410
• Geographic Distribution of E-shopping: Application of Structural Equation Models in the Twin Cities
  Abstract: The proliferation of internet shopping has imposed enormous pressure on traditional stores. Few studies have examined the geographic distribution of online buyers and its implications on retail development. Using 585 internet users in the Minneapolis-St. Paul metropolitan area, this study develops structural equation models to test two competing hypotheses regarding the connections between spatial attributes and e-shopping: diffusion of innovation and efficiency. The results demonstrate that the influence of shopping accessibility on e-shopping is not uniform, but depends on the locations in metropolitan areas. Specifically, internet users living in urban and/or high shopping accessibility areas tend to purchase online more often than their counterparts in other areas because the former are better educated and use the internet more heavily than the latter. However, low shopping accessibility in exurban areas does promote the usage of e-shopping, compared to exurban areas with relatively high shopping accessibility.
  Authors: Cao, Xinyu; Chen, Qian; Choo, Sangho
  Authors: Cao, Xinyu; Chen, Qian; Choo, Sangho
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 815
  Paper Number: 13-0474
• Will Privacy Concerns Limit the Ability of Smart Phone Technologies to Help Foster Collaborative School Travel?
  Abstract: The GPS functionality in modern Smartphones has the capability of pinpointing an individual’s position at any given time. As a result, a wide variety of apps are now available, providing the user with location-specific services, tailored to their location in space and time. In a transportation sense, such functionality has potential for providing users with visibility of current and future potential transport options. Understanding where an individual is, where they have been and might be in the immediate future, and knowledge of their typical schedules and historic trace patterns means that opportunistic, collaborative travel opportunities might be possible. A key issue with such a concept, however, is the extent to which individuals are prepared to share information on their whereabouts, schedules and travel habits with others. This concept is being explored as part of the 6th Sense Transport project and this paper looks specifically at using smartphone technology to visualise lift-sharing opportunities for the morning school run, and the associated privacy issues.Findings from a study of parents of primary-age children suggested that such a ‘real-time’ travel option visualisation system (RTOVS) must consider both who a user’s personal information is given to and the type of information given to be successfully adopted by users. This is because the benefits it offers must outweigh the privacy risks perceived by the users. Additionally, the survey results indicated that such a system will be particularly attractive to the educated, employed, high-income household with time-scheduling pressures.
  Authors: Cruickshanks, Scott; Cherrett, Tom; Waterson, Ben; Norgate, Sarah; Davies, Nigel; Speed, Chris; Dickinson, Janet
  Authors: Cruickshanks, Scott; Cherrett, Tom; Waterson, Ben; Norgate, Sarah; Davies, Nigel; Speed, Chris; Dickinson, Janet
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0525
• Analyzing Effect of All-Red Intervals in Crash Reduction: Case Study of Heckman Correction for Urban Signalized Intersection Crashes
  Abstract: All-Red (AR) interval is designed as a method of clearance interval to safely clear vehicles that enter the intersection dilemma zone. The provision of AR is generally expected to reduce the occurrence of crashes, though there are situations that AR is not proved to be effective because it is used at intersections with a higher potential for crashes. This controversial result however, does not indicate that the AR interval is a contributing cause of crashes. Therefore, the self-selection bias of signal designs needs to be corrected when estimating their effect in improving safety. To address the selection-bias problem at signalized intersections, a Heckman two-stage approach is adapted. First, a probit model is developed to explain the interrelationship between the AR interval and highway geometry, traffic volume, and environmental variables. Second, the selection bias term (or Heckman correction) is included in the second stage to build two negative binomial models for locations with and without an AR interval. Further, average treatment effects (ATE) and effect of treatment on the treated (TT) are estimated to examine the effect of AR intervals on the whole sample and treated sample, respectively. Three-year crash data on urban signalized intersections in the Detroit metro area is used to validate the proposed models. The results show that a random intersection with an AR interval will reduce crashes by 36 percent when compared to a non-AR interval intersection. For treated intersections (with AR interval) there is a 51 percent reduction of total crashes compared to intersections without treatment (if not designed with AR interval). The AR interval is a meaningful advance in reducing crashes by 15 percent. Key words: Self-selection bias, Heckman Two-step correction model, All-Red Interval, Probit Model, Negative Binomial Model
  Authors: Mishra, Sabyasachee; Zhu, Xiaoyu
  Authors: Mishra, Sabyasachee; Zhu, Xiaoyu
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-0548
• PROBE VEHICLE BASED STATEWIDE MOBILITY PERFORMANCE MEASURES FOR DECISION MAKERS
  Abstract: Decision makers in state transportation agencies typically manage budgets approaching or exceeding $1B. However, the data they have historically used for making investment decisions is quite coarse and is typically based upon short-term volume counts fed into models to forecast future performance. As a result, it is not uncommon for construction projects to address needs that were forecast to be a priority five to ten years prior, while more pressing congestion challenges go unmet. This fact does not go unnoticed by the public and media, and it is essential that long-term planning begin to be supplemented by more current performance measures. Emerging private sector probe vehicle data obtained from mobile phones and commercial telemetric providers offers an opportunity to augment traditional forward-looking planning models with performance measures that reflect conditions motorists are experiencing today. This paper proposes analytical probe data reduction techniques that can be scaled to a project, region, state, or national level to create technically sound yet intuitive mobility performance measures of current freeway conditions. These types of performance measures are increasingly used by high-level agency management to identify locations where customers experience congestion, to determine the magnitude of congestion, and to compare congestion on various highway corridors. These proposed performance measures can be used for policy-oriented decisions such as prioritization of capital program investments, managing snow removal, and scheduling lane closures. In addition to the analytical data reduction, corresponding data visualizations of the performance measures are presented. This paper describes the application of these analytical techniques to seven Indiana interstates comprised of 1886 directional miles. These interstates span rural and urban sections that experience varying levels of recurring and non-recurring congestion due to special events, winter weather, and construction activity. Specific examples adjacent to the Indianapolis, Indiana; Louisville, Kentucky; and Chicago, Illinois, metro areas are presented along with the Top 10 congested Interstate segments.
  Authors: Brennan, Thomas M.; Remias, Stephen Matthew; Grimmer, Gannon; Horton, Deborah K.; Cox, Edward D; Bullock, Darcy M.
  Authors: Brennan, Thomas M.; Remias, Stephen Matthew; Grimmer, Gannon; Horton, Deborah K.; Cox, Edward D; Bullock, Darcy M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Policy
  Session: A0030T
  Paper Number: 13-0551
• Time-of-Day Dynamics of Episodic Hedonic Value of Activities and Travel
  Abstract: In this paper a preliminary analysis of episodic reports of feelings are analyzed to explore the correlation with activity and travel characteristics, personal and household circumstances as well as other contextual factors that may influence feelings. Interestingly, a strong correlation is found between global indicators of satisfaction about life, health, and finances and discrepancies with marriage satisfaction. Very important, however, is the finding that different types of activities are significantly associated with many different scores of feelings with some of them varying by time of day in a way that is as expected (tired and pain) but not uniformly across indicators of subjective well being. Travel as a passenger is consistently a pleasant activity while traveling alone is associated with positive and negative feelings. In addition, interaction with social networks is an important correlate of episodic feelings. Strong correlation between person and household characteristics and episodic reports, on the other hand, is also found. Moreover, the role enacted within a household and companionship in activities are also important correlates of feelings. Where persons live (region of the US) and living arrangements (retiree communities and elderly housing) are also correlates of emotions.
  Authors: Goulias, Konstadinos G.
  Authors: Goulias, Konstadinos G.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0521
• Using Time-Based Metrics to Compare Crash Risk Across Modes and Locations
  Abstract: The objective of this work is to identify better metrics of exposure when comparing traffic crash risk across modes or across locations. We propose that total time travelled should be used for road user exposure to crash risk. The idea behind this is that travel time reflects the differences in speeds across different modes and hence should be used as the basic exposure metric from which crash risk based on other metrics, such as travel distance, can easily be derived. We also propose that when comparing crash risk of different modes across different locations the time based mode share should be used as an explanatory variable. By using mode share we are generalizing the safety in numbers concept which focuses on absolute numbers. This work presents a discussion on why these two metrics were chosen and how they are different from the commonly used metrics. Quantitative evidence for the choice of time based metrics is also presented using travel survey data to compare crash risk across modes and locations.
  Authors: Guler, Sukran Ilgin; Grembek, Offer; Ragland, David R.
  Authors: Guler, Sukran Ilgin; Grembek, Offer; Ragland, David R.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-0522
• Quality Control for Weigh-in-Motion Data Incorporating Threshold Values and Rational Procedures
  Abstract: One of the major improvements with using the Mechanistic-Empirical Pavement Design Guide (MEPDG) occurs in its characterization of traffic. Instead of converting all Class 4 to Class 13 truck axles to 18,000 lb equivalent single axles (ESALs), the MEPDG simulates every truck axle, and the associated stresses and strains imposed on the pavement structure, from a wide range of axle load spectra (ALS). For this reason, the MEPDG needs traffic inputs in more detail than previous empirical pavement design methods, and thus, a higher requirement of weigh-in-motion (WIM) data quality. This paper presents a new and objective approach to quality control (QC) of WIM data to ensure data quality for pavement design purposes. Instead of using subjective visual comparisons of gross vehicle weight (GVW) distributions, this research implements a peak-range check, peak-shift check and correlation analysis to quantify the ALS comparison process of rational checks. A number-of-axles check that calculates the average number of axles per vehicle class is also introduced herein. The entire QC procedure has been applied to 12 WIM stations in Alabama. As a result, 30.6% of data were filtered out, and data from one entire WIM station were removed. Therefore, QC of WIM data is strongly recommended, regardless of the extent of WIM system calibration.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-0606
• Correlation-Based Clustering of Traffic Data for Mechanistic-Empirical Pavement Design
  Abstract: Development of traffic data clusters is crucial for use of the mechanistic-empirical pavement design guide (MEPDG) when site-specific traffic data are not available, but statewide data are too general. In current clustering practice, subjective decisions are made on issues such as determination of the number of clusters. This paper presents a new clustering combination method, correlation-based clustering, that can be used to quantify similarity of traffic data from different sites as an input to the clustering process. For each particular traffic input required in the MEPDG, the similarity between two sites is evaluated using Pearson’s correlation coefficient. This approach evaluates the sensitivity of pavement design thickness to each traffic input in order to quantify cut locations of hierarchical clustering trees, and thereby determine the number of clusters in an objective manner. The MEPDG requires many traffic inputs, including vehicle class distributions, four types of axle load spectra (per vehicle class), monthly and hourly distribution factors, and distributions of axle groups per vehicle. This clustering approach is performed for each traffic input such that a unique set of clusters can be developed for each traffic input. This method has been implemented for 22 direction-specific WIM stations to identify clusters of sites with similar pavement performance for each traffic input of the MEPDG. This paper illustrates the clustering process for one traffic input (single axle distribution) and also presents clustering results for vehicle class distribution.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Authors: Mai, Derong; Turochy, Rod E.; Timm, David H.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-0607
• Dynamic Route Choice Behavior Analysis Considering En Route Learning and Choices
  Abstract: This paper presents a method to model a driverfs en-route learning process and changes in route choice at each decision node. A model based on Bayesian networks (BN) is proposed to describe the en-route updating of the driverfs knowledge of the traffic state. A random utility-based model is developed to predict en-route choices. A case study based on probe data is carried out to illustrate the development of the model and analyze the dynamic route choice problem. The results show that the model in which a driverfs choice of making en-route decisions is taken into account has a better goodness of fit. The probability of making an en-route choice is related to the distance from the origin and the spatial scale of the intersection at the decision node.
  Authors: Li, Dawei; Miwa, Tomio; Morikawa, Takayuki
  Authors: Li, Dawei; Miwa, Tomio; Morikawa, Takayuki
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-0646
• Identifying Chosen Public Transport Connections from GPS Observations
  Abstract: Transport planners around the world are currently searching for innovative strategies for customer-friendly and efficient public transport systems. An important element in this process is the understanding of the passengers' valuation of different elements of public transport trips. One challenge associated with this the observation of the actual passenger behaviour in all its complexity. One way to address this challenge is to use person-based GPS devices for observing the public transport connections chosen by passengers. GPS-based studies have become increasingly popular in the last two decades and their advantages for observing and modelling car and bicycle route choice have been shown by many studies. However, for public transport connection choice modelling the processing routines to extract the chosen connections and their relevant attributes have so far been missing.This paper reports on a first implementation of such a procedure called "public transport map-matching". The basic idea is to first employ a car map-matching procedure for each stage of a public transport trip to determine the route within the public transport network. Then, this route is used to find the most likely public transport line and the respective boarding and alighting stops. Finally, the stages of the public transport trip are joined together including the access and egress stages by walk or bicycle. The procedure is tested using the data from an ongoing GPS study in Zurich - an area in Switzerland with a very dense public transport network.
  Authors: Rieser-Schüssler, Nadine; Axhausen, Kay W.
  Authors: Rieser-Schüssler, Nadine; Axhausen, Kay W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-0588
• Arterial Incident Detection Procedures Utilizing Real-Time Vehicle Reidentification Travel Time Data
  Abstract: Travel time data obtained from vehicle re-identification systems is becoming increasingly available due to the implementation of various technologies such as license plate recognition, automatic toll collection systems, inductive loop signature systems, and Bluetooth-based wireless vehicle identification. Travel time data obtained in real-time from such systems is used to update estimated travel times displayed on variable message signs, and research has also been conducted that utilizes travel time data as inputs to incident detection algorithms. Implementation of such systems and prior research has primarily focused on freeways and other free-flowing roads. However, such systems for travel time data collection are also being implemented on arterials. In this research an incident detection procedure that utilizes point-to-point travel time data obtained from an arterial vehicle re-identification system is developed and evaluated. Historical travel time data provided by a Bluetooth-based travel time data collection system, and reported incident data are utilized to evaluate the procedure. The results show that the procedure provides a good balance of detection and false alarm rates.
  Authors: Kim, David Sungsup; Park, SeJoon; Ko, Seng-Seok; Yu, Wooyeon
  Authors: Kim, David Sungsup; Park, SeJoon; Ko, Seng-Seok; Yu, Wooyeon
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-0161
• Cycling Habits and Other Psychological Variables Affecting Commuting by Bicycle in City of Madrid
  Abstract: In order to develop effective cycling policies it is important to know the factors influencing the use of the bicycle for daily mobility. Traditional discrete choice models tend to be based on variables such as time and cost, which do not sufficiently explain the choice of the bicycle as a mode of transportation. Since psychological factors have been identified as particularly influential in the decision to commute by bicycle, this paper examines the perceptions of different cycling factors, and their influence on commuting by bicycle. Perceptions are measured using attitudes, other psychological variables, and habits.Statistical differences in the variables are established according to the choice of commuting mode and bicycle experience (commuter, sport/leisure, no use). This enabled us to identify the main barriers to commuting by bicycle, and to make recommendations for cycling policies. We identify two underlying structures (factors) among the attitudinal variables: “Direct Benefits” and “Long-term benefits”; and three other factors related to variables of difficulty: “Physical conditions”, “External facilities”, and “Individual capacities”. The effect of attitudes and other psychological variables on individuals’ decision to cycle to work/place of study is tested using a logit model. In the case study of Madrid (Spain), the decision to cycle to work/place of study is heavily influenced by cycling habits (for non-commuting trips). Since bicycle commuting is not common, attitudes and other psychological variables play a less important role in the use of bikes.
  Authors: Muñoz López, Begoña; Monzon, Andres; Lois, David
  Authors: Muñoz López, Begoña; Monzon, Andres; Lois, David
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0624
• Identifying Differences in Travel Time Budgets Between Elderly and Nonelderly Groups Using PSL Structural Equation Models: Case Study for Seoul Metropolitan Area, South Korea
  Abstract: To date aging is one of the most important issues in our society because of its significant socio-economic impacts. Corresponding concerns about the transportation needs of the elderly have led to a focus on the mobility and quality of life of the elderly and motivated various studies of senior mobility. In particular, the frequency of seniors' travel activities heavily relies on how far and easily they can travel. It is of great interest to explore travel behavior of the elderly. This study is to investigate the difference of travel behavior between the elderly and the non-elderly groups focusing on travel time budget (TTB), using 2006 household travel diary survey data in Seoul Metropolitan Area. We develop PLS-structural equation models to identify major variable to affect TTB of the two groups and then compare the differences between the models. The model results indicate that the significant variables to have effects on TTB are different between the two groups, and their degrees of effects of the same variables are also different with respect to personal and household characteristics.
  Authors: Kim, Taeho; Choo, Sangho; Shin, Yeacheol; You, Soyoung Iris
  Authors: Kim, Taeho; Choo, Sangho; Shin, Yeacheol; You, Soyoung Iris
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0643
• Feasibility of Incorporating Reliability Analysis in Traffic Safety Investigation
  Abstract: In this paper, the method of reliability analysis has been employed to investigate the feasibility of using it in traffic safety analysis. The reliability analysis approach, frequently used to evaluate the probabilities of failures for a specific structural system, has two main outcomes which are the reliability index and design points. Two different approaches to use these two outcomes in traffic safety analysis have been presented in this paper. Data from a mountainous freeway in Colorado was used. The reliability index was utilized to evaluate the hazardous freeway segments by incorporating the traffic flow parameters provided by radar detectors. The design points were employed to predict the crash occurrence at the disaggregate level with weather parameters. Finally the results from both approaches have been compared to the results from a traditional method, and the reliability analysis method showed promising applications in traffic safety. By using the reliability indexes, the three most hazardous segments are consistent with the results from the crash rates segment ranking approach; for the design points, by utilizing these thresholds the accuracy rate of predicting crash occurrence could be improved by 10% compared to the logistic regression method.
  Authors: Yu, Rongjie; Shi, Qi; Abdel-Aty, Mohamed A.
  Authors: Yu, Rongjie; Shi, Qi; Abdel-Aty, Mohamed A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-0477
• Integrated Transportation Payment System Security and Privacy Breaches: Extent of the Problem and Simulated Case Study
  Abstract: This research investigates the security and privacy breaches of electronic Integrated Transportation Payment Systems, ITPS, via Radio-Frequency Identification, RFID, tags and smart cards, their frequency of occurrence and type. This National Science Foundation, NSF, funded study has created a website that collects news events reporting breaches worldwide and automatically categorizes them by various characteristics, including five defined categories for security types of breaches and five categories of privacy breaches. A preliminary statistical analysis reports the existing extent of the problem in electronic ITPS.A second objective requires investigation of the impact on traffic operations due to the adoption of security protection measures or software algorithms. One case study, a toll collection facility on the Massachusetts Turnpike is simulated in PTV Vision VISSIM traffic software for various transaction times. This ITPS is a ticketing tolling payment system located on the I-90 east-west Turnpike in Massachusetts, USA. Simulations were performed with and without added times at the point of the payment transaction. Initial results indicate that the impact on operations is negligible for security measures that add milliseconds of transaction time. However, for added transaction times in a range of seconds, the impact is more significant.
  Authors: Zarrillo, Marguerite; El Lazkani, Elia; Prairie, David; Spilhaus, Tyler
  Authors: Zarrillo, Marguerite; El Lazkani, Elia; Prairie, David; Spilhaus, Tyler
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Policy
  Session: 325
  Paper Number: 13-0650
• Crash-Type Propensity Analysis with Bayesian Models Using Microscopic Traffic and Weather Data
  Abstract: This study investigates a range of effects of microscopic traffic and weather factors and roadway geometry information on the specific crash type for a mountainous freeway. Crashes have been categorized as rear-end, sideswipe and single-vehicle crashes. Six-minute Automatic Vehicle Identification (AVI) segment average speed, real-time weather data and roadway geometry data are utilized as explanatory variables in this study. First, two binary logistic regression models were estimated by comparing single-vehicle to multi-vehicle crashes and sideswipe crashes to rear-end crashes. Then a full model which simultaneously fits two conditional logistic regression models (mixed logit model) for the three crash types has also been estimated. Results from the models indicate that single-vehicle crashes are more probable in the snow season, at moderate slopes, three-lane segments, under the free-flow conditions; while the sideswipe crash occurrence differs from rear-end crashes with the visibility situation, number of lanes, grades and their directions (up or down). Moreover, the results of the Bayesian random effects logistic regression models have been compared with the results from the classic logistic regression with the Frequentist and Bayesian inference techniques. It was demonstrated that the Bayesian random effects logistic regression outperforms the other two approaches with higher accuracy and lower Brier scores. The innovative way of estimating two conditional logistic regression models simultaneously in the Bayesian framework fits the data structure well. Conclusions from this study imply that different active traffic management strategies should be designed for three- and two-lane roadway sections and also considering the seasonal effects.
  Authors: Yu, Rongjie; Abdel-Aty, Mohamed A.; Ahmed, Mohamed M.; Wang, Xuesong
  Authors: Yu, Rongjie; Abdel-Aty, Mohamed A.; Ahmed, Mohamed M.; Wang, Xuesong
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-0718
• Multi-objective Optimization Model And Evolutionary Algorithm To Plan Uav Cruise Route For Road Traffic Surveillance
  Abstract: Unmanned Aerial Vehicle (UAV) was used to collect traffic information of road segments not installed with traffic detectors, therefore, it¡¯s necessary to plan UAV cruise route for traffic surveillance so as to minimize UAV cruise cost as much as possible. First, a multi-objective optimization model of planning UAV cruise route was proposed, which aimed to minimize UAV cruise distance and minimize the number of UAVs used respectively. Then, an evolutionary algorithm based on Pareto optimality technique was proposed to solve multi-objective UAV cruise route planning problem. Next, a case using UAV to monitor 14 road segments near Tongji University in China was studied, the case results showed that optimized cruise distance and the number of UAVs used were reduced by 38.54% and 33.33% respectively compared to the initial optimal solutions, this demonstrated that the proposed evolutionary algorithm was feasible and effective. Finally, some discussions of using UAVs for traffic surveillance were given.
  Authors: Li, Li
  Authors: Li, Li
  Year: 2013
  Document Type: Paper
  Subject: Construction; Data and Information Technology; Design
  Session: 729
  Paper Number: 13-0735
• Development of Various Artificial Neural Network Car-Following Models with Converted Data Sets by Self-Organization Neural Network
  Abstract: This paper presents the development of a car-following model using the multilayer artificial neural network (ANN) structure. Four ANN car-following models were developed with various input variables in the car-following behavior. Tens of thousands of data points were used for the model developments, including acceleration from start, deceleration to stop, and mid to high speed car-following conditions on a test track. A four-layer neural network structure was set up and a genetic algorithm (GA) was utilized to determine the initial synaptic weights among the neurons based on the observed data sets. Back-propagation methodology was then utilized for fine tuning the synaptic weights further, however the models sometimes had a difficulty in learning such enormous number of raw data points. Therefore, a methodology of data point conversion was developed with, Kohonen Feature Map (KFM), a self-organization neural network model. The converted fewer data points were used for training the models. The results with and without data conversion were compared. In order to evaluate the ANN models, the existing well-known car-following model, the GM model, was calibrated with the same data sets. This paper concluded that the ANN models were successfully developed with KFM data conversion without deteriorating the original data quality. One of the four ANN models performed better than the GM car-following model. In comparing the results among the four ANN models, it was implied that the accelerations of the following vehicle and leading vehicle can also become key input variables for improving the modeling of car-following behavior.Keywords: Car-Following Model, Artificial Neural Networks (ANN), Back-propagation, Kohonen Feature Map (KFM), Genetic Algorithm (GA), Data Sampling, Microscopic Traffic Mode
  Authors: Tanaka, Mitsuru; Nakatsuji, Takashi
  Authors: Tanaka, Mitsuru; Nakatsuji, Takashi
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 530
  Paper Number: 13-0787
• Travel Behavior Change After Introduction of Public Bicycle Systems: Case Study in Minhang District, Shanghai, China
  Abstract: The paper presents the first step of a series research on the characteristics of public bicycle users¡¯ travel behavior and the underlying mechanisms to support the development of public bicycle systems (PBS) in China. Based on a questionnaire survey in Minhang District, Shanghai, the paper focuses on travel behavior change after the introduction of the PBS. Using statistical analyses, it is found that people travel slightly more often than before when using PB; their travel distances are longer than expected. However, most users ride PB as a replacement of public transit, walking and private bicycle. Few modal shifts happened from car and moped/motocycle. Convenience contributes most to people¡¯s modal shift to PB, much more than the second and third most important factors, saving time and exercising, which is further confirmed by estimating a binary logit model explaining modal choice behavior between PB and other transport modes. The estimated travel utility gain based on the model turns out to be significant. The charging experiment reveals that charging PB rental fee can reduce PB use extensively, much more than compensating for long distance ride.
  Authors: Zhu, Wei; Pang, Yuqi; Wang, De; Timmermans, Harry J.P.
  Authors: Zhu, Wei; Pang, Yuqi; Wang, De; Timmermans, Harry J.P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting
  Session: 735
  Paper Number: 13-0764
• Longitudinal GPS Travel Data and Breach of Privacy via Enhanced Spatial and Demographic Analysis
  Abstract: Longitudinal GPS travel data provide a wealth of information related to travel behavior and on-road vehicle behavior that are very valuable to researchers. Sharing the data publicly allows researchers to explore the data and create new knowledge beyond the initial research objectives. However, if any data are to be used outside of a secure server, the data must be processed in such a manner that ensures the confidentiality of the data will not be breached. High resolution GPS data (e.g. second-by-second speed and location information), when associated with the individual households or drivers, compromises privacy and have a significant potential to harm human subjects. This paper explores how data from the Commute Atlanta Study could be processed to make it useful to researchers while protecting the privacy of the participants. The research developed and assessed methodologies designed to identify the individual participants’ home location from processed data and then tested analytical datasets for breach of privacy.The research effort found that the home location can be identified to within reasonably small neighborhoods and when the household demographic information are included within the datasets (which is necessary for researchers) exact households can be identified. While there may be some new data processing approaches that could be used to eliminate privacy concerns, until such systems are developed and proven to be not breachable through rigorous analysis, the Georgia Tech team has determined that researchers should access the high-resolution data within controlled secure labs and that the datasets should not be made public without undertaking additional efforts to ensure that home locations cannot be identified when external data sources are leveraged in the analyses.
  Authors: Elango, Vetri Venthan; Khoeini, Sara; Xu, Yanzhi; Guensler, Randall
  Authors: Elango, Vetri Venthan; Khoeini, Sara; Xu, Yanzhi; Guensler, Randall
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Policy
  Session: 325
  Paper Number: 13-0820
• Empirical Evidence on Ratio of Means Problem and Estimation of Values of Time with Stated Preference Data
  Abstract: Values of time calculated as the ratios of time and cost parameters for groups of individuals do not correspond to the average of the individual values of time where these individual values are heterogeneous. This is known as the ratio of means problem. Empirical evidence on the implications of the ratio of means problem for value of time estimation is provided in the form of a meta-analysis of 31 sets of binary choice stated preference data for car drivers. A deterministic, cost-minimizing methodology is used to estimate individual values of time for each data set. Meta-regression analysis reveals systematic between-study variation related to the proportion of non-traders in the data. Comparison of the averages of the individual values of time with the corresponding values of time derived from binary logit models shows that the latter values tend to be significantly lower across a range of sensitivity tests, even under conservative assumptions. Awareness of the ratio of means problem and its potential consequences is important, particularly for meta-analyses or benchmarking exercises that include values of time derived using a variety of methodologies. It is recommended that in future, methodologies for estimating values of time that explicitly allow for heterogeneity should be preferred. For binary choice data with small numbers of attributes, the deterministic cost-minimizing methodology presented here is recommended as a useful complement to more computationally intensive techniques.
  Authors: Mitrani, Alex
  Authors: Mitrani, Alex
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0828
• Evaluation of Postencroachment Time as a Surrogate for Opposing Left-Turn Crashes
  Abstract: Highway safety evaluation has traditionally been performed using crash data though this method has limitations in terms of timeliness and efficiency. Previous studies show that the use of surrogate safety data allows for faster evaluation of safety in comparison to the significantly longer time horizon required for collecting crash data. However, the predictive capability of surrogate measures is still an area of ongoing research. Previous studies have often resulted in inconsistent findings for the relationship between surrogates and crashes, one of the primary reasons being inconsistent definitions of a conflict. This study evaluates the effectiveness of Post Encroachment Time (PET) as a surrogate measure for evaluating the propensity of crashes between left-turning vehicles and opposing through vehicles at 4-legged signalized intersections. The primary method of data collection is through video recording with post-processing using custom semi-automatic video processing software to reduce the video to a useable format ready for analysis. The study evaluates the effectiveness of PET as a surrogate measure by comparing three variations of PET measures with crash history. This comparison shows that a threshold value of PET plays an important role in establishing its correlation with crashes with the best results at a threshold as low as one second.
  Authors: Peesapati, Lakshmi; Hunter, Michael P.; Rodgers, Michael Owen
  Authors: Peesapati, Lakshmi; Hunter, Michael P.; Rodgers, Michael Owen
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-0839
• Exploring the Impact of Unfamiliar Transit Travel on Attitudes and Behavior
  Abstract: Past research has found that unfamiliar travel on public transport can be an unpleasant experience while research in psychology has shown first impressions to be integral to all attitude development due to a phenomenon referred to as the ‘primacy effect’. However the ‘primacy effect’ concept has never been explored in the context or urban transit. This paper explores the experience of unfamiliar travel and its potential importance by comparing first trip experiences, which in this study context means first time using public transport to travel to a university campus, with perceptions of overall trip experiences through a university access survey. The results show that unfamiliar travel by transit tends to be a more negative experience than familiar trips. ‘Ease of navigation’ (wayfinding), ‘emotional state’, ‘ease of navigating transfer’, and ‘ease of ticketing’ were particularly negative aspects of first trips. Unfamiliar travel was found to be significantly correlated with overall ratings of transit suggesting a strong basis for the ‘primacy effect’ in public transport. Results also suggest that first trip experiences are significantly correlated with subsequent travel behaviour but only for ‘choice travellers’ i.e. those with access to a car and not for ‘captive’ transit users. This is a novel research area with important implications for travel behaviour and user attitude research. Suggestions for future research are relevance to transport practitioners are made.
  Authors: Schmitt, Lorelei; Currie, Graham; Delbosc, Alexa
  Authors: Schmitt, Lorelei; Currie, Graham; Delbosc, Alexa
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0946
• Use of Principal Component Analysis to Deal with Class Imbalance Problem for Traffic Incident Detection
  Abstract: High imbalance occurs in real-world where the traffic incident detection system is aimed to detect a rare but important case - incident case. Traffic incident detection can be treated as a task of learning classifiers from imbalanced or skewed datasets. Based on principal component analysis (PCA), a one-class classifier for incident detection is constructed from the major and minor principal components of normal instances. The experiments are conducted with a real traffic data collected from A12 highway in the Netherlands. The parameters setting, including the significance level, the percentage of the total variation explained and the upper bound of the eigenvalues for the minor components are discussed. The testing results demonstrate that this method achieves better performance comparing with partial least squares regression. It is shown to be a promising method for traffic incident detection.
  Authors: Changjiang, Zheng; Chen, Shuyan; Wang, Wei; Lu, Jian
  Authors: Changjiang, Zheng; Chen, Shuyan; Wang, Wei; Lu, Jian
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-0935
• Probability Distortion in Multiattribute Decisions: From Risk to Ambiguity
  Abstract: Transport users face complex decisions. Not only the consequences of their decisions are uncertain, but they generally involve several attributes, such as time and money. Time-money tradeoffs have been intensively studied in transport economics, and a growing attention is now paid to users' attitudes towards uncertainty related to transport decisions. The present paper makes two contributions to the transportation literature: one theoretical and the other experimental. First, we propose a fast and tractable method for measuring Prospect Theory parameters capturing attitudes towards probabilities (decision weighting function) and attitudes towards losses (loss aversion parameter). The elicitation method does not involve the value function and is particularly suitable in complex multi-attribute decisions were the shape of the value function is unknown.Second, we present the results of an experiment that uses the proposed elicitation method to measure, at individual level, probability distortion in decisions involving both time and money consequences in two contexts: risk (where probabilities are given) and ambiguity (where the probability distribution is unknown). An original experimental setup that exposes subjects to real gains and losses for money and time is built for the purpose. Inverse S-shaped probability weighting and loss aversion is observed for risk, and probability distortion is more pronounced in ambiguity.
  Authors: Kemel, Emmanuel; Paraschiv, Corina
  Authors: Kemel, Emmanuel; Paraschiv, Corina
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0978
• Modewise Travel Time Estimation on Urban Arterials Using Transit Buses as Probes
  Abstract: The accurate estimation of travel time of different types of vehicles in a traffic stream has always been of interest in various stages of planning, design, operations and evaluation of transportation systems. The traditional way of travel time data collection by means of active test vehicles or license plate matching techniques has its own limitations in terms of cost, manpower, geographic coverage, sample size and accuracy. With the growing need for real-time travel time data, the passive probe vehicles with onboard Global Positioning Systems (GPS) is increasingly being used. However, due to privacy issues and participation requirements, the public transit vehicles are the only ones which can be equipped with GPS devices and this could possibly be used as a source to estimate the travel time of other types of vehicles. The present study is an attempt in this direction. Two approaches have been proposed: one based on the ratio of the section travel times of public transit to other vehicles and other one based on the quantifiable relationship between the public transit and other vehicles section travel times. As the dwell time at bus stops is a unique characteristic of transit buses when compared to other vehicles in the stream, a methodology has been proposed to find the dwell times based on the approaching and departing speeds at bus stops. The results showed that the second approach based on relationship between the bus and other vehicles section travel times performs better.
  Authors: Kumar, Vasantha; Vanajakshi, Lelitha Devi
  Authors: Kumar, Vasantha; Vanajakshi, Lelitha Devi
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-1022
• Spatial Analysis of Fatal and Injury Crashes in Flanders, Belgium: Application of Geographically Weighted Regression Technique
  Abstract: Generalized Linear Models (GLMs) are the most widely used models utilized in crash prediction studies. These models illustrate the relationships between the dependent and explanatory variables by estimating fixed global estimates. Since the crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is examined by means of calculating Moran’s I measures for dependent and explanatory variables. The results indicate the necessity of considering the spatial correlation when developing crash prediction models. The main objective of this research is to develop different Zonal Crash Prediction Models (ZCPMs) within the Geographically Weighted Generalized Linear Models (GWGLM) framework in order to explore the spatial variations in association between Number of Injury Crashes (NOICs) (including fatal, severely and slightly injury crashes) and other explanatory variables. Different exposure, network and socio-demographic variables of 2200 Traffic Analysis Zones (TAZs) are considered as predictors of crashes in the study area, Flanders, Belgium. To this end, an activity-based transportation model framework is applied to produce exposure measurements while the network and socio-demographic variables are collected from other sources. Crash data used in this study consist of recorded crashes between 2004 and 2007. GWGLMs are developed using a Poisson error distribution and are often referred to as Geographically Weighted Poisson Regression (GWPR) models. Moreover, the performances of developed GWPR models are compared with their corresponding GLMs. The results show that GWPR models outperform the GLM models; this is due to the capability of GWPR models in capturing the spatial heterogeneity of crashes.
  Authors: Pirdavani, Ali; Brijs, Tom; Bellemans, Tom; Wets, Geert
  Authors: Pirdavani, Ali; Brijs, Tom; Bellemans, Tom; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1049
• Using multi-source GPS data to characterize multiday driving patterns and fuel use in a large city region
  Abstract: The paper describes the use of GPS data obtained from both commercial and project-specific sources to examine the travel behavior and fuel consumption patterns of drivers over a three-day period in Gauteng Province, South Africa. Data for commercial (truck and light delivery vehicle) traffic are obtained from a commercial fleet management provider, which continuously tracks the movements of 42,000 vehicles. Data for private car users come from a panel of 720 drivers, whose multiday driving activity is tracked using mobile passive GPS loggers. We analyze and compare the driving behavior of the two driver populations in terms of total distance travelled, spatial patterns (e.g. the amount of travel on different road types) and temporal variations (e.g. variations across time of day and across multiple days). The detailed nature of GPS data also permits the estimation of fuel consumption at a very disaggregate level (by link and time of day), and the identification of differences between user groups, which have significant implications for transport and energy policy. We identify research needs related to the collection and integration of GPS data from multiple sources for model calibration and program evaluation.
  Authors: Venter, Christoffel; Joubert, Johan W.
  Authors: Venter, Christoffel; Joubert, Johan W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 299
  Paper Number: 13-1033
• Accessibility to Urban Parks in Montreal from the Perspective of Children
  Abstract: Parks are elemental components of urban environments that provide environmental value and serve valuable social functions. In particular, urban parks provide spaces for physical activity and may help reduce the risk of obesity and other adverse health outcomes. In order to enjoy the beneficial opportunities for activities in parks, users must have reasonable access to these resources. A starting point for inquiries about park utilization and the potential benefits of urban green spaces is an assessment of their geographical accessibility. Of particular interest, in terms of potential users of parks, are children, whose geographical range is limited by their ability to traverse space using non-motorized modes of transportation, or by their dependence on adults for common forms of motorized mobility. The objective of this paper is to measure accessibility to urban parks from the perspective of children traveling by walking in the island of Montreal, Canada. We evaluate the relationship between the distribution of children population and conditions of accessibility to urban parks, in order to understand the potential for use and possible spatial disparities in the distribution of valuable environmental resources. Implementation of accessibility measures is supported by statistical analysis of trip length using Montreal’s 2008 Household Travel Surveys database. Estimates of trip length for a desired child profile, based on attributes such as age, gender, income class, family structure, as well as geographical location are used to calculate accessibility to urban parks. This research contributes to the assessment of the distribution of access to urban parks by children, and can inform planners and policy makers in order to improve the supply of public facilities (parks) from a transportation perspective.
  Authors: Reyes, Mario; Paez, Antonio; Morency, Catherine
  Authors: Reyes, Mario; Paez, Antonio; Morency, Catherine
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1058
• Multivariate Spatial Models of Excess Crash Frequency at Area Level: Case of Costa Rica
  Abstract: Recently, areal models of crash frequency have being used in the analysis of various area-wide factors affecting road crashes. On the other hand, disease mapping methods are commonly used in epidemiology to assess the relative risk of the population at different spatial units. A natural next step is to combine these two approaches to estimate the excess crash frequency at area level as a measure of absolute crash risk. Furthermore, multivariate spatial models of crash severity are explored in order to account for both frequency and severity of crashes and control for the spatial correlation frequently found in crash data. This paper aims to extent the concept of safety performance functions to be used in areal models of crash frequency. A multivariate spatial model is used for that purpose and compared to its univariate counterpart. Full Bayes hierarchical approach is used to estimate the models of crash frequency at canton level for Costa Rica. An intrinsic Multivariate Conditional Autoregressive model is used for modeling spatial random effects. The results show that the multivariate spatial model performs better than its univariate counterpart in terms of the penalized goodness-of-fit measure Deviance Information Criteria. Additionally, the effects of the spatial smoothing due to the multivariate spatial random effects are evident in the estimation of excess equivalent property damage only crashes.
  Authors: Aguero-Valverde, Jonathan
  Authors: Aguero-Valverde, Jonathan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-1061
• Leveraging the General Transit Feed Specification (GTFS) for Efficient Transit Analysis
  Abstract: Since 2007, the transit industry has benefited from a widely adopted data standard called the General Transit Feed Specification (GTFS) which has enabled the development of numerous traveler information tools, namely transit trip planners. The purpose of this project is to demonstrate the potential for GTFS feeds to be used as a data source for transit analyses such as those found in the Transit Capacity and Quality of Service Manual. Three primary project tasks include an analysis of GTFS field usage by different agencies; an analysis of a single agency at the stop, route and system level; and a batch analysis and comparison of 50 large transit agencies in North America. The experience of developing scripts and database queries for this project compared to alternatives such as “screen-scraping” schedules from transit websites or parsing printed schedules suggests that GTFS is a highly efficient data source and proves the importance of broadly accepted data standards. The methodology documented in this paper and the open-source scripts, which have been made available online, will be useful for any analyst or researcher who has tasks related to analyzing single or multiple transit systems at the stop, route or system level.
  Authors: Wong, James Christopher
  Authors: Wong, James Christopher
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 299
  Paper Number: 13-1070
• Reducing Severity of Crashes During Holidays: Are We Targeting the Right Behaviors?
  Abstract: Holidays are times of recreation, rest and relaxation to be enjoyed with our loved ones. Hence, any road traffic accidents and the subsequent deaths and injuries tend to receive more media attention and evoke stronger public reactions because they are more tragic as they turn our merriment into grief and mourning. Consequently, many jurisdictions have implemented more aggressive police enforcement and publicity campaigns targeted at reducing risky driving behaviors during the holidays. However, relatively little formal research has been conducted to specifically identify the factors contributing to crashes during holidays. Using data from 1999-2008, this research endeavours to identify the behavioral factors that statistically and significantly contribute to the severity of holiday crashes involving two-vehicles. In addition, the impact of different control variables formed from crash, vehicle, road surface and other behavioral factors will also be explored. Our results indicate that drivers’ violation, drivers’ error, drivers’ intoxication and non-use of seat-belts significantly contribute to increasing the severity of holiday crashes. However, the impact of unsafe speeding is found to be insignificant in the study. The results obtained suggest that it may be time to consider a more balanced approach to the road safety blitzes conducted during holidays.
  Authors: Anowar, Sabreena; Yasmin, Shamsunnahar; Tay, Richard
  Authors: Anowar, Sabreena; Yasmin, Shamsunnahar; Tay, Richard
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1095
• Using Mobile Apps to Measure Spatial Travel-Behavior Changes of Carsharing Users
  Abstract: Positioning technologies in commercially-available mobile phones have matured significantly over the last five years, offering new opportunities to collect high resolution spatial travel behavior data for transportation research and operations. This paper discusses the use of a global positioning system mobile phone application, TRAC-IT, to collect travel behavior data of carsharing users as part of a variable pricing experiment. A random sample of 30 participants carried a mobile phone with TRAC-IT installed, resulting in over 4 million GPS data points that provided precise geographic and spatio-temporal information. These data informed an analysis of the participants’ geographic footprint by estimating a set of standard-distance ellipses of carsharing and non-carsharing modes. Spatial analysis results show that carsharing users have a much smaller activity space (0.5 square miles) than individuals not using carsharing over the same period (7.8 square miles). The activity space of carsharing users contracts while using carsharing as a mode of transport (0.2 square miles for carsharing versus 0.5 square miles for other modes). This may be because carsharing users do not have access to a private vehicle and, therefore, rely on carsharing to conduct out-of-home required trips for maintenance activities, such as grocery shopping.
  Authors: Concas, Sisinnio; Barbeau, Sean J.; Winters, Philip L.; Georggi, Nevine Labib; Bond, Julie M.
  Authors: Concas, Sisinnio; Barbeau, Sean J.; Winters, Philip L.; Georggi, Nevine Labib; Bond, Julie M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 765
  Paper Number: 13-1107
• Accuracy of Geo-imputation: An Approach to Capture Micro-Environment
  Abstract: The role of built environment in travel behavior has seen increased interest in strategic transportation planning. To capture relationships between travel behavior and the built environment, micro-environment variables representing infrastructure and land uses surrounding trip origins and destinations are being used as explanatory variables in travel demand models. Buffers of various sizes can be created around origins or destinations in order to capture the micro-environments. A key requirement is to know the exact latitude/longitude of the location. However, such information is commonly removed from public use data due to privacy concerns. To assess if synthetic geo-imputed residences can overcome the removal of exact location information, two North Carolina activity-based travel survey datasets (the Research Triangle survey, N=4,724 and Charlotte survey, N=3,310) were analyzed. The fundamental question is whether the geo-imputed micro-environmental measurements can be used to sufficiently accurately model travel behavior. Comparisons were conducted between actual residences, geo-imputed residences and residences assumed to be located at centroids of census blocks (as is current practice). The results indicate that: 1) census block centroid assignment results in statistically significant systematic errors when calculating the accessibility measures; 2) geo-imputation based on TAZ level can provide reasonably accurate accessibility measures in larger buffer sizes of 0.75 miles, but not in smaller buffers of 0.25 miles; 3) geo-imputation based on census block level provided reasonably accurate accessibility measures that were sufficiently accurate for specifying travel behavior models.
  Authors: Wang, Xin; Khattak, Asad J.; Chen, Juyin
  Authors: Wang, Xin; Khattak, Asad J.; Chen, Juyin
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0700
• Enhancing External Cordon Travel Forecasting Methods for International Border Areas: Tour-Based Analysis of Mexican Residents’ Travel in San Diego County, California
  Abstract: In San Diego County, California, residents of Mexico make an estimated 350,000 trips daily and account for twenty-one percent of weekday boardings on the local light rail system. To adequately plan for this market, a border intercept survey and activity diary was used to develop a tour-based microsimulation model of travel made by Mexican residents within the region. Given an exogenous macroeconomic forecast of the total number of border crossings, the model predicts the volume of travelers using each port of entry, the locations of primary destinations within San Diego County, the frequency and locations of intermediate stops, the modes of travel across the border and between stateside locations, and the contributions from Mexican residents to highway and transit facility usage in the United States. The model’s design is compared and contrasted with typical external cordon methods and recently developed bi-national models. Empirical results show that the sensitivity of external cordon travel forecasting methods to characteristics of international border areas can be substantially enhanced with this approach.
  Authors: Hood, Jeffrey; Freedman, Joel; Sun, Wu; Ouyang, Ziyang; Samarin, Alex
  Authors: Hood, Jeffrey; Freedman, Joel; Sun, Wu; Ouyang, Ziyang; Samarin, Alex
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-0892
• Exploring Behavioral Responses of Motorists to Risk-Based Charging Mechanisms
  Abstract: This paper reports on the behavioural response of motorists to a variable rate charging scheme designed to encourage safer driving practices and reduce exposure to crash-risk – specifically kilometres driven, night-time driving and speeding. The study involved a five-week ‘before’ period of GPS monitoring to establish how motorists drove normally, followed by a five-week ‘after’ period of GPS monitoring in which charges were levied and changes assessed. Incentives were paid to motorists for the difference in the charges between the two five-week periods. Vehicle kilometres travelled (VKT) were reduced by ten percent, although the sample was evenly split by those increasing VKT compared to those decreasing VKT. The proportion of distance speeding fell by 4.7 percent, which when coupled with decreases in VKT, implied a net reduction of kilometres spent speeding of over 40 percent. Three-quarters of the sample reduced their speeding. Exit interviews with a cross-section of participants highlighted the practical difficulties of reducing kilometres, but (more encouragingly) reinforced the potential to reduce speeding.
  Authors: Greaves, Stephen; Fifer, Simon
  Authors: Greaves, Stephen; Fifer, Simon
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1128
• Realignment of Road Network Maps with GPS Tracking Data
  Abstract: Road network datasets are widely available either for a fee or for free on the Internet. Unfortunately, some of them are not always accurate and up-to-date. These inaccuracies could cause navigation errors and prove costly to users. Therefore, it is important to devise a useful, efficient and cost effective method to make the datasets more accurate. One way to rectify the dataset quality is to use GPS data collected by GPS enabled navigation devices. When the map is not accurate it is reasonable to assume that the GPS data is more accurate than the map. Thus, GPS tracks can be used to realign the traveled street segments. One can view this as the inverse of the map matching problem. Instead of matching GPS positions to the map, we match the map to GPS tracks (or points).This paper outlines a comprehensive approach for realigning street segments to GPS data collected from moving vehicles. The process includes GPS data filtering, matching GPS points to existing road segments, shifting the road segments to the GPS points and forming new intersections and vertices. The end result of the process is a revised map of the road segments in their corrected positions. For each of these tasks new algorithms or enhanced existing algorithms were developed and employed. The proposed process was successfully implemented on real world data and the results of the realigned road segments are shown, analyzed and verified. The realigned network showed full agreement with high accuracy orthophoto of the test area.
  Authors: Greenfeld, Joshua
  Authors: Greenfeld, Joshua
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 793
  Paper Number: 13-1139
• Innovative Online Research Tools Investigating Attitudes Toward Cars Among Young People
  Abstract: Young people are less car-reliant, a worldwide trend documented in US, Europe and Australian contexts. However little research explains how attitudes are shaping these trends. Popular hypotheses are the (i) changing social status of the car, (ii) growing role of electronic communications and (iii) growing environmental awareness, but no academic research has directly explored these issues.This paper uses innovative online research tools to explore these issues with young people. While the research was qualitative a range of common themes emerged. In general results support the hypothesis that cars have less social status in terms of prestige however they were still considered an important aspect of maturity and adulthood and of critical value for mobility Social status and the car may thus have changed from being a luxury to one of maturity. How this affects car travel is unclear.Results support the view that electronic communications are of growing importance although they are not replacing face to face interaction and unlikely to be reducing travel. Young people spoke passionately about the importance of time spent with friends and emphasised how transport could facilitate/ hinder this. It is difficult to see this as a strong basis for reduced car orientation.Not one person in the sample spontaneously mentioned that environmental concerns shaped their travel choices. Even when prompted these concerns were far removed from travel decisions.The paper concludes with a discussion of key findings, discusses the effectiveness of the methods used and outlines future areas for research in this field.
  Authors: Delbosc, Alexa; Currie, Graham
  Authors: Delbosc, Alexa; Currie, Graham
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1141
• Modeling of Spatial Transit Mode Choice Based on Smart Card Data in Seoul
  Abstract: In this study, using public transport smart card data observed in Seoul, Korea, we provide empirical evidence for the existence of a spatial correlation among transit mode choices at the Traffic Analysis Zone TAZ level. The Bayesian hierarchical modeling framework was applied to construct both spatial associations among TAZ levels and among commonly used utility functions with travel time and fare. We consider the binomial regression model with spatial effect by using a conditional autoregressive model (CAR) and regard a passenger¡¯s choice of metro rather than bus transport as a reference category. The results show that the areas with a higher probability that passengers will choose a bus are clustered and that those regions have fewer metro stations than bus stations. We also found the spatial correlation is statistically meaningful and potentially useful in the modeling of a spatial transit mode choice. Consequently, a reliable spatial interaction would constitute valuable information for transportation agencies in terms of their route planning and scheduling based on the transit smart card data.
  Authors: Eom, Jin Ki; Park, Man Sik; Heo, Tae-Young; Stone, John R.
  Authors: Eom, Jin Ki; Park, Man Sik; Heo, Tae-Young; Stone, John R.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 530
  Paper Number: 13-1142
• Identifying Primary and Secondary Accidents from Spatiotemporal Accident Impact Analysis
  Abstract: The identification of secondary accidents is accompanied by the definition of the primary accident impact area. Although the accident impact area varies with the geometric characteristics of roads and periodic characteristics of traffic flow as well as with accident types, most previous studies used a fixed boundary to identify secondary accidents and primary accidents. Thus, the objective of this research is to develop a method to define the spatio-temporally different boundaries varying with different types of accident. Based on the developed boundaries, the secondary accident is identified in the primary accident location as well as in its opposite direction. Secondary accidents in the same and opposite directions were identified to be 8.1% and 3.7% of total primary accidents, respectively. Also, only 0.4% of total primary accidents were connected with the secondary accident both in the same and opposite directions. Although the proposed method seems to be complicated, the results from the method will be useful to understand secondary accident characteristics in more realistic analysis through the spatio-temporal accident impact area in the accident direction as well as in its opposite direction. Specifically, they can be used by public sector transportation agencies in making operational strategies for reducing the secondary accidents on freeways.
  Authors: Chung, Younshik
  Authors: Chung, Younshik
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1148
• Exploring the Properties of Mean-Variance Relations in Freeway Travel Times
  Abstract: Travel time estimation models have been widely studied in transportation field. However, the variation in the mean and standard deviation of travel times has been much less investigated. A temporary decrease in capacity (e.g. congestion caused by an active bottleneck) leads to a quite significant difference in the standard deviation of travel time for congestion onset and dissipation periods. This phenomenon results in hysteresis loops where the periods in congestion offset exhibit a higher or a lower travel time variance than the ones in congestion onset with the same mean travel time. The aim of this paper is to identify empirical reasons that cause the hysteresis phenomenon. Within this framework, using an analytical expression of travel time and closed form expression of mean and variance, hysteresis loops are reconstructed. This allows us to decompose the problem into its components. Factor analysis is implemented to identify which components cause the difference between onset and offset periods, and lead to a hysteresis pattern in mean-standard deviation curve.
  Authors: Yildirimoglu, Mehmet; Koymans, Anne; Geroliminis, Nikolas
  Authors: Yildirimoglu, Mehmet; Koymans, Anne; Geroliminis, Nikolas
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-1179
• Optimal Method for Traffic Accident Case Retrieval and Evaluation
  Abstract: An optimal method for traffic accident case retrieval has been proposed to improve accuracy of case retrieval. This method aims to assist users in decision-making in real-time under traffic accident conditions. And a new evaluation index called matching degree, as supplement of case similarity, is proposed for assessing the retrieved case set comprehensively. Different from previous studies, the presented optimal method and evaluation index have the following four critical features: (1) proposing an information entropy method to evaluate dispersion of traffic accident data and determining the weight value of each traffic accident case feature objectively; and (2) establishing a traffic accident case retrieval base which contains several sub-case bases, and that puts a solid foundation for equalizing case retrieval; then (3) proposing a global similarity model of traffic accident cases and two equations for calculating local similarity of numerical traffic data and categorical traffic data; and (4) presenting a new evaluation index called matching degree firstly, make up deficiency of the original evaluation index. This study develops a prototype system for traffic accident case retrieval experiments. Dozens of case retrieval experiments have demonstrated the promise of this optimal case retrieval method and evaluation method for traffic accident management in real-time.
  Authors: Dong, Xianyuan
  Authors: Dong, Xianyuan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 618
  Paper Number: 13-0913
• Assessing Impacts of Teleworking Policy on Crash Occurrence: Case of Flanders, Belgium
  Abstract: Travel demand management (TDM) consists of a variety of policy measures that affect the effectiveness of transportation systems by changing travel behavior. The primary objective of such TDM strategies is not to improve traffic safety, although their impact on traffic safety should not be neglected. The main purpose of this study is to simulate the traffic safety impact of conducting a teleworking scenario (i.e. 5% of the working population engages in teleworking) in the study area, Flanders, Belgium. Since TDM strategies are usually conducted at a geographically aggregated level, crash prediction models (CPMs) should also be developed at an aggregate level. Given that crash occurrences are often spatially heterogeneous and are affected by many spatial variables, the existence of spatial correlation in the data is also examined. The results indicate the necessity of accounting for the spatial correlation when developing crash prediction models. Therefore zonal crash prediction models (ZCPMs) within the Geographically Weighted Generalized Linear Modeling (GWGLM) framework are developed to incorporate the spatial variations in association between the number of crashes (NOCs) (including fatal, severe and slight injury crashes recorded between 2004 and 2007) and other explanatory variables. Different exposure, network and socio-demographic variables of 2200 traffic analysis zones (TAZs) are considered as predictors of crashes. An activity-based transportation model framework is adopted to produce detailed exposure metrics. This enables to conduct a more detailed and reliable assessment while TDM strategies are inherently modeled in the activity-based models. In this study, several ZCPMs with different severity levels and crash types are developed to predict the NOCs for both the null and the teleworking scenario. The models show a considerable traffic safety benefit of conducting the teleworking scenario due to its impact on the reduction of total Vehicle Kilometers Traveled (VKT) by 3.15%. Implementing the teleworking scenario is predicted to reduce the annual VKT by 1.426 billion and total NOCs to decline by 2.62%.
  Authors: Pirdavani, Ali; Brijs, Tom; Bellemans, Tom; Kochan, Bruno; Wets, Geert
  Authors: Pirdavani, Ali; Brijs, Tom; Bellemans, Tom; Kochan, Bruno; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 815
  Paper Number: 13-1050
• ATIS: Interpretation of Bayesian Neural Network for Predicting the Duration of Detected Incidents
  Abstract: Predicting the required duration of detected incidents is crucial and challenging for more safe and efficient traffic incident management program. Many machine learning methods have been suggested in the literature to tackle this problem. Neural networks, especially, have attracted a lot of interests in recent years mainly because of their universal approximation property. In this paper, Bayesian Neural Network (BNN) model yields satisfactory accuracy superior to other models. However, neural networks are regarded to be hard to interpret because the learned knowledge is generally hidden from the user, and the models became no more than just ‘black boxes’. This limitation is solved by using the algorithm TREPAN that imitates the nature of neural networks in extracting decision trees. In contrast with shortcomings of traditional decision tree, TREPAN not only facilitates better comprehensibility with M-of-N expression but maintains high predictive accuracy to its respective network. Extracted decision trees provide a discovery and explanation of previously unknown relationships present in incident nature, and represent a series of decisions to assist emergency response personnel in better decision making. Furthermore, to quantify the importance of variables from the neural network, connection weight approach is used. Those factors appearing in the first splitter of decision tree show high relative importance indicating that they are influential for incident duration, consistent with the findings in preliminary analysis. This knowledge also helps emergency operators determine which incident cases have more priority under resource limitations, and highlights the potential factors to be improved.
  Authors: Park, Hyoshin; Zhang, Xin; Haghani, Ali
  Authors: Park, Hyoshin; Zhang, Xin; Haghani, Ali
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 482
  Paper Number: 13-1214
• Linking Elderly Transport Mobility and Subjective Well-being: Multivariate Latent Modeling Approach
  Abstract: It is widely accepted that mobility is critical for social integration in a complex urban society and is essential to the maintenance of life satisfaction and well-being. Subjective well-being has recently become a topic of interest within the transportation research community. In this paper we aim at understanding the fundamental linkages between subjective well-being or happiness and transport mobility/travel behavior of the elderly population. The research here is based on data from Disability and Use of Time (DUST) 2009, which specifically targets senior couples with an average age of 68 years. Using scores to a set of satisfaction questions about life, health, memory, finances, marriage, we estimate latent class clusters. This leads to four distinct clusters of respondents depending on the degree of happiness in each of the satisfaction questions. Using the membership to each cluster as a dependent variable, we estimate ordered probit and multinomial logistic regression models to study the relationship between clusters and individual characteristics including socio-demographics, activity patterns, time use and use of active modes (walking/bicycling). The results show that respondents who are engaging in activities out of home, socializing and enjoy better mobility, also report higher levels of subjective well-being leading to a better quality of life. The model findings also show that illness and pain are related to lower well-being and that quality of life in older age is correlated to mobility.
  Authors: Ravulaparthy, Srinath; Yoon, Seo Youn; Goulias, Konstadinos G.
  Authors: Ravulaparthy, Srinath; Yoon, Seo Youn; Goulias, Konstadinos G.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1242
• Testing and Comparing Neural Network and Statistical Approaches for Predicting Transportation Time Series
  Abstract: The paper compares univariate and multivariate neural network and autoregressive time series models with application to short-term forecasting of freeway speeds. The developed models are evaluated with respect to temporal data resolution, prediction accuracy, and quality of fit using statistical tests. Results indicate that neural networks provide - by and large - more accurate predictions than classical statistical approaches particularly for finer data resolutions. Evaluation of model fit indicates that, in contrast to vector autoregressive models, Neural Networks may also provide unbiased predictions. Overall, our findings clearly suggest the need to jointly consider statistical and Neural Network models in order to develop more efficient prediction models.
  Authors: Vlahogianni, Eleni I.; Karlaftis, Matthew G.
  Authors: Vlahogianni, Eleni I.; Karlaftis, Matthew G.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 482
  Paper Number: 13-1167
• Evaluation of Effectiveness of Automatic Crash Information Notification Systems on Freeways
  Abstract: The automatic crash information notification system (ACINS) is a well-known technology with promising potential to reduce the crash response time (CRT) of emergency medical services. Reducing CRT will contribute to saving the lives of and alleviating the severity of injuries for crash victims. To fully operate the ACINS, it is important to quantify the safety benefits, which is fundamental for justifying public investment. This study proposed a methodology for quantifying the effectiveness of the ACINS and applied the methodology to the Korean freeway system. The proposed methodology consists of three steps. Fist, a statistical model was developed to predict injury severity using ordered logistic regression. Second, the amount of reduced CRT that would result from the ACINS was estimated. The effectiveness of the ACINS, which are defined as the number of reduced fatalities and severe injuries, were derived after considering the market penetration rate (MPR). When the proposed methodology is applied to 2010 freeway crash data, the result that fatalities are reduced by 11.8-18.1% when there is a 100% MPR. The outcomes of this study support decision making for public investments and for establishing relevant traffic safety policies.
  Authors: Jeong, Eunbi; Oh, Cheol; Kim, Taehyung; Kim, Ikki
  Authors: Jeong, Eunbi; Oh, Cheol; Kim, Taehyung; Kim, Ikki
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 614
  Paper Number: 13-1269
• Vehicle Re-identification for Travel Time Measurement Based on Loop Detectors Considering Lane Changes
  Abstract: This study develops the vehicle re-identification algorithm for travel time measurement on expressway based on loop detector data. Travel time is one of the most valuable information among traffic information and is necessary for the effective traffic operation and management, though travel time measurement is still challenging. In this study, we propose the methodology that the lack of vehicle signature information from loop detectors is complemented and enriched by models. Concretely, lane-changing models estimating the probabilities that a vehicle at upstream station will change the lane and be observed in the other lane at downstream station and that a gap observed at upstream will be occupied by some vehicles from the other lanes are established. Then, the estimation of these probabilities as well as the similarity of vehicle signatures is simultaneously considered in the re-identification algorithm. As a result of the application to the expressway in Japan where loop detectors are installed with at most 2 km distance, it was revealed that by considering these probabilities, the accuracy of vehicle re-identification and measured travel time much improved. In addition, though it is critical for the algorithm to give the appropriate parameters to the model, the parameters which were adjusted to the specific traffic situation could robustly present the good-fit results even in the other traffic situation.
  Authors: Shiomi, Yasuhiro; Ogawa, Takayuki; Uno, Nobuhiro; Shimamoto, Hiroshi
  Authors: Shiomi, Yasuhiro; Ogawa, Takayuki; Uno, Nobuhiro; Shimamoto, Hiroshi
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-1294
• Quantifying Road Grade Based on In-Vehicle Measurements with Global Positioning System Receivers
  Abstract: Variability in real-world vehicle fuel use and emissions during a trip depends primarily on vehicle speed, acceleration, and road grade. However, there is not a standard method for measuring road grade from a moving vehicle. Changes in road grade of more than a percentage point significantly affect fuel use and emission rates. Consumer grade Global Positioning System receivers with barometric altimeter (GPS/BA) are used to measure position and elevation. Data were collected from 12 vehicles, each using 3 GPS receivers, for a total of 36 repeated GPS/BA runs on eight one-way routes in the Research Triangle Park, NC region. Road grade was estimated by combining data from 9, 18, and 36 runs and applying linear regression to non-overlapping and adjacent road segments of length d. The accuracy of the estimated road grade was evaluated based on comparison to estimates from aircraft-based LIDAR measurements. The average grade is found to be accurate. The average precision is 0.39, 0.25, and 0.16 percentage points, for sample sizes of 9, 18, and 36 runs, respectively, among 1,116 individual road segments. The proportion of segments that have road grade precision within a target of +/-0.5 percentage points are 80 percent for 9 runs, 98 percent for 18 runs, and 99.8 percent for 36 runs. Thus, the use of a low cost GPS/BA is a promising approach for accurate and precise measurement of grade relative to data quality needs for quantifying variability in fuel use and emissions.
  Authors: Yazdani Boroujeni, Behdad; Frey, H. Christopher
  Authors: Yazdani Boroujeni, Behdad; Frey, H. Christopher
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 423
  Paper Number: 13-1417
• Role of Commuter Benefits in Shaping Decision to Walk, Cycle, or Ride Transit to Work in Washington, D.C., Region
  Abstract: This study examines the relationship between commuter benefits and the likelihood to walk, cycle, or ride public transport to work in the Washington, DC region. The analysis examines individual level commute data along with information about multiple categories of commuter benefits, such as free car parking, public transport benefits and workplace facilities for cyclists and pedestrians. Data about full-time workers originate from the 2007/2008 Washington, DC Household Travel Survey. Results of a multinomial logistic regression model indicate that free car parking is significantly associated with lower levels of commuting by public transport as well as less walking and cycling to work. Public transport benefits are associated with higher levels of commuting by public transport as well as more walking and cycling to work. Benefits for walking and cycling are associated with higher levels of walking and cycling to work, as well as public transport use. Employees simultaneously offered free car parking, public transport benefits, and benefits for walking and cycling are significantly less likely to choose public transport. This suggests that free car parking may effectively counterweigh the incentives for walking, cycling, and public transport when benefit packages include free car parking alongside incentives for other modes. Results for control variables have expected signs and most are significant. Limitations of the study, relating to endogeneity, selection bias, and omitted variables, are discussed. These findings are consistent with other studies of commuting in the Washington, DC region as well as other studies of transportation mode choice and commuter benefits.
  Authors: Hamre, Andrea; Buehler, Ralph
  Authors: Hamre, Andrea; Buehler, Ralph
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting
  Session: 735
  Paper Number: 13-1429
• Transit to Eternal Youth: Life-cycle and Generational Trends in Greater Montreal Public Transport Mode Share, Canada
  Abstract: Young people appear to be using public transit more than their predecessors, reversing 20th century trends, but the importance of such findings depends on whether high transit use persists as these riders age. This paper examines whether transit mode share for commuting trips is increasing; socio-economic and geographic trends are also explored to attempt to determine whether these trends are likely to continue. The study uses repeated cross-sectional origin-destination surveys of the Greater Montreal region (1998, 2003 and 2008). Over 45,000 home-to-work trips are studied for each survey year. Transit use growth between 2003 and 2008 is high and relatively universal, possibly reflecting 2008 period conditions such as a rapid gasoline price spike; as such, 2008 data are viewed with caution. Nevertheless, a general lifecycle pattern of decreasing transit share with age is apparent within cohorts until individuals reach their early 30s, followed by decades of stability. This pattern appears to hold in recent years, but with higher youth use rates, and it is argued that the higher use will continue as current younger cohorts mature. Suburbanization by those in their early 30s is evident and, along with household composition changes, appears to explain much of the final within-cohort mode share declines before equilibrium. Transit providers might see lasting ridership gains, as those currently in their early 30s and younger replace lower-use cohorts in the workforce, provided service provision keeps pace. Addressing the needs of young people, whose mode choices are comparatively unsettled, should be a priority for transit agencies.
  Authors: Grimsrud, Michael A.; El-Geneidy, Ahmed M.
  Authors: Grimsrud, Michael A.; El-Geneidy, Ahmed M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1438
• Redesigning Black Spots in Traffic: Effect Evaluation
  Abstract: This study evaluates the safety effects of an extensive black spot program that has been implemented in Flanders-Belgium. Based on their crash history, 800 locations were selected as black spots. The study evaluates 134 locations that were redesigned between 2004 and 2007. The adopted approach is an Empirical Bayes before-and-after study that accounts for effects of general trends and for the stochastic nature of crashes, including regression to the mean. Two different comparison groups were established. Dependent on the applied comparison group, the analyses showed a decrease in the number of injury crashes of 24 to 27%, significant at the 1%-level. A separate analysis for crashes with serious or fatal injuries showed a decrease of 40 to 52%, also significant at the 1% level. ANOVA-analyses were made to check whether differences in effects occur depending on the characteristics of the location or the implemented intersection design. The results suggest a more favourable evolution for intersections that were priority controlled in the before situation compared with signal-controlled intersections. Crash reductions were also higher at locations with a lower traffic volume compared to locations with a higher volume.
  Authors: De Pauw, Ellen; Daniels, Stijn; Brijs, Tom; Hermans, Elke; Wets, Geert
  Authors: De Pauw, Ellen; Daniels, Stijn; Brijs, Tom; Hermans, Elke; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1465
• Crash Fault Analysis of Out-of-State Drivers in Vermont
  Abstract: This study examined single- and two-vehicle police-reported crashes in Vermont between 2003 and 2008. It evaluated the likelihood of being at fault for Vermont drivers versus out-of-state drivers. Analysis using odds ratios estimated that out-of-state drivers are 98% more likely to be at-fault for a single-vehicle crash and 9% more likely to be at-fault for a two-vehicle crash.Age, gender, season of year, light conditions, and road type were statistically significant interactions for Vermont and out-of-state drivers for single-vehicle crashes. Male drivers and driving during the winter months had more pronounced effects of increasing single-vehicle crash fault for out-of-state drivers than for Vermont drivers. Vermont drivers, on the other hand, were more apt to cause a crash on gravel roads.The interactions were less pronounced for two-vehicle crashes. Being male or an older driver increased crash odds for both groups. Driving during the summer months increased out-of-state drivers crash odds by 21%, while it was insignificant for Vermont drivers. The other factors tested were insignificant for both groups.The crash evaluation of fault for “foreign” drivers’ crashes has been understudied in the United States. Previous research, conducted mostly in other countries, has been limited but has shown that foreign drivers are more likely to be involved in a crash. This study in Vermont strongly suggests the need for further study of this factor as well as identification of associated interventions.
  Authors: Harootunian, Kristine; Aultman-Hall, Lisa; Lee, Brian H. Y.
  Authors: Harootunian, Kristine; Aultman-Hall, Lisa; Lee, Brian H. Y.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1597
• Traffic Incident Detection Using Random Forest
  Abstract: This paper presents the applications of random forest in traffic incident detection. The detection performance is evaluated by the common criteria including detection rate, false alarm rate, mean time to detection, classification rate and the area under the curve of the receiver operating characteristic (ROC). Different from decision tree, random forest uses a combination of classification trees instead of a single tree to construct random forest model. This model can improve the average performances in traffic incident detection just by voting the decision tree classifiers. Two experiments are performed to investigate the potential application of random forest to traffic incident detection from the perspective of classification strength and correlation. Random forest trains many individual decision tree classifiers to construct the classifier ensemble, and then uses this classifier ensemble to detect the traffic incidents. Consequently, it needs to train many times. Compared with decision tree, the training time cost of decision tree is much lower, which is because of decision tree only need train one time. The detection performance of the random forest was compared to multi-layer feed forward neural networks (MLF) which yield superior incident detection performance in the previous studies. The experimental results indicate that random forest is competitive with MLF.
  Authors: Liu, Qingchao; Lu, Jian; Chen, Shuyan
  Authors: Liu, Qingchao; Lu, Jian; Chen, Shuyan
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-1610
• Indexing Crashworthiness and Crash Aggressiveness by Major Car Brands
  Abstract: This study aims at indexing crash worthiness and crash aggressivity of 23 major car brands in Florida with consideration of the brand origin. It contributes to the literature by proposing a method for redefining the safety performance of cars by taking into account the cars¡¯ hazardousness imposed to counterpart cars that are involved in the same crashes. A Bayesian hierarchical ordered logistic model was applied to relate the injury severity level of drivers to crash compatibility of car brands. In the models, we assume that the driver injury depends on the difference of the striking cars¡¯ aggressivity and the struck cars¡¯ self-protectiveness in two-vehicle crashes with external factors controlled. A total of 17,178 two-vehicle-crash records with 34,356 car involvements in Florida were used in the investigation. The results show that most of the premium cars such as Volvo, Cadillac, Infiniti and Lexus possess excellent crash worthiness and relatively low crash aggressivity. Self-protection abilities of popular car brands such as Ford, Toyota, Honda and Chevrolet vary considerably, but their hazardousness perform similarly and are lower than the average level. European cars perform relatively good self-protection but are also more hazardous to the counterpart cars when crashes occur. Japanese cars show lower worthiness and aggressivity than American cars, while South Korean cars are associated with the lowest crash worthiness and mean crash aggressivity.
  Authors: Huang, Helai; Hu, Shuiyan; Abdel-Aty, Mohamed A.
  Authors: Huang, Helai; Hu, Shuiyan; Abdel-Aty, Mohamed A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1754
• Decision Support System for Smart Growth Innovation in Urban Midwest: GIS Connection Between Brownfield Site Redevelopment and Transportation
  Abstract: This paper documents the design and development of a prototype web-based data distribution system for brownfield site redevelopment in the urban Midwest. The system is designed to support smart growth initiatives through the application of innovative technology for economic redevelopment and sustainable utilization of brownfield sites in Toledo, Ohio. Many Midwestern cities have experienced industrial decline that has led to a preponderance of brownfield sites, particularly in poorer urban core areas. Brownfield sites are typically situated along existing and often deteriorating infrastructure. Greater efficiency in economic development can be gained by linking transportation infrastructure resources with brownfield remediation. In addition, communities gain countless health, safety, environmental and revenue benefits through the identification and remediation of brownfield sites. A lack of data resources is one major barrier to redevelopment of these sites. The system developed here seeks to reduce that barrier by providing a user interface and information delivery system to support the identification and reuse of brownfield sites for policy and decision-makers; this methodology and design can be replicated for use in other regions to further promote smart growth. Detailed here is the development and implementation of an interactive web-based geographic information system (GIS) designed as a user-centered decision support tool to augment policymakers’ and stakeholders’ site selection and infrastructure capital investment decisions in support of brownfield remediation and development. This system thus provides not only a comprehensive data delivery tool and decision support system but also serves as a template for application in other urban regions.
  Authors: Schafer, Sarah E; Lindquist, Peter S,.
  Authors: Schafer, Sarah E; Lindquist, Peter S,.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 618
  Paper Number: 13-1721
• Examining Trip Underreporting Behavior Using GPS-Assisted Household Travel Surveys
  Abstract: Trip underreporting has been a persistent and well known problem with household travel surveys. This paper primarily focus on investigating the pattern and magnitude of trip underreporting behavior by comparing travel data from diary-based and GPS-assisted surveys, and exploring a wide range of demographic and travel related characteristics in the aim of gauging trip misreporting. This study employs the New York metropolitan region household travel survey, which contains about 1,900 (10% of the entire sample) households participated in the GPS-assisted prompted recall method instead of diary-based approach. Detailed trip underreporting phenomenon by trip purpose, mode, trip length, trip chaining, and time-of-day, etc. is explored across various socioeconomic and demographic characteristics, such as person type, gender, household size, and household income, etc. This paper sheds lights on the multi-faceted dimension and the associated factors of trip misreporting, which will leads to better methods to account for misreporting in travel surveys and to incorporate correction factors in model estimation.
  Authors: Jin, Xia; Wu, Jingcheng; Asgari, Hamidreza; Argote, Jorge A.
  Authors: Jin, Xia; Wu, Jingcheng; Asgari, Hamidreza; Argote, Jorge A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-1780
• Road Safety Forecasts in Five European Countries Using Structural Time-Series Models
  Abstract: Modeling road safety development is a complex task, which needs to consider both the quantifiable impact of specific parameters, as well as the underlying trends that cannot always be measured or observed. The objective of this research is to apply structural time series models for obtaining reliable medium- to long-term forecasts of road traffic fatality risk, using data from five countries with different characteristics from all over Europe (Cyprus, Greece, Hungary, Norway and Switzerland). Two structural time series models are considered: (i) the local linear trend model and the (ii) latent risk time-series model. Furthermore, a structured decision tree for the selection of the applicable model for each situation (developed within the DACOTA research project) is outlined. First, the fatality and exposure data that are used for the development of the models are presented and explored. Then, the modeling process is presented, including the model selection process, the introduction of intervention variables and the development of mobility scenarios. The forecasts using the developed models appear to be realistic and within acceptable confidence intervals. The proposed methodology is proved to be very efficient for handling different cases of data availability and quality, providing an appropriate alternative from the family of structural time series models in each country. A concluding section providing perspectives and directions for future research is finally presented.
  Authors: Antoniou, Constantinos; Papadimitriou, Eleonora; Yannis, George
  Authors: Antoniou, Constantinos; Papadimitriou, Eleonora; Yannis, George
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-1786
• Assessment of Exposure Proxies for Macroscopic Road Safety Prediction
  Abstract: Road safety is a major global health problem and no effort should be spared in trying to limit its impacts. Modeling road safety is a complex task, which needs to consider both the quantifiable impact of specific parameters, as well as the underlying trends that cannot always be measured or observed. Macroscopic data are often not available, or not in the form that they are desired. Therefore, it is often required to attempt to consider alternative sources of data, which may be correlated with the modeled phenomenon. The objective of this research is to investigate the suitability of alternative proxy variables for macroscopic road safety modeling, using three suitable exposure proxies: (i) number of vehicles in circulation, (ii) GDP and (iii) fuel consumption. Several structural time-series models have been developed for each proxy for two Mediterranean countries with many similar socio-economic characteristics: Greece and Cyprus.Based on the findings of this analysis, a number of observations can be drawn. Proxy variables can provide reasonable results, when exposure data are not available. Furthermore, even in two countries with many similarities the selected proxy measure differs. This suggests that the underlying conditions that make a variable a suitable proxy for exposure is complex and needs further investigation.
  Authors: Antoniou, Constantinos; Yannis, George
  Authors: Antoniou, Constantinos; Yannis, George
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1788
• Analyzing Relationship Between Car Generation and Severity of Motor-Vehicle Crashes in Denmark
  Abstract: While in the last 40 years Danish roads have observed a decrease in the number of fatalities, research has not investigated the contribution of legislative, enforcement, technological, infrastructural and human factors to this reduction. In the context of a Danish car market with remarkably high registration tax causing potential buyers to hold longer onto old cars, the relationship between technological enhancements of vehicles and severity of crashes requires particular attention. The current study investigates the relationship between car generation (i.e., car’s first registration year) and injury severity sustained by car drivers involved in accidents in Denmark between 2004 and 2010. A generalized ordered logit model is estimated while controlling for several characteristics of the crash, the vehicle and the persons involved, and scenario analysis is performed for assessing the effect of car generation on drivers’ injury severity. Results illustrate that newer car generations are associated to significantly lower probability of injury and fatality, and that replacing older cars with newer ones introduces significant and not to be overlooked benefits for both population and society.
  Authors: Rich, Jeppe Husted; Prato, Carlo Giacomo; Hels, Tove; Lyckegaard, Allan; Kristensen, Niels Buus
  Authors: Rich, Jeppe Husted; Prato, Carlo Giacomo; Hels, Tove; Lyckegaard, Allan; Kristensen, Niels Buus
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1246
• Predicting Freeway Crash Likelihood and Severity with Real-Time Loop Detector Data
  Abstract: Real-time crash risk prediction using traffic data collected from loop detector stations is useful in dynamic safety management systems aimed at improving traffic safety through application of proactive safety countermeasures. The major drawback of most of the existing studies is that they focus on the crash risk without consideration of crash severity. This paper presents an effort to develop a model that predicts the crash likelihood at different levels of severity with a particular focus on severe crashes. The crash data and traffic data used in this study were collected on the I-880 freeway in California, United States. This study considers three levels of crash severity: fatal/incapacitating injury crashes (KA), non-incapacitating/possible injury crashes (BC), and property-damage-only crashes (PDO). The sequential logit models were developed to link the likelihood of crash occurrences at different severity levels to various traffic flow characteristics derived from detector data. The fitness and prediction capability of the forward and backward versions of the models were compared to select a better alternative. The results show that the sequential structure (forward vs. backward) does not have considerable impact on the model¡¯s fitness and predictive capabilities. More interestingly, the traffic flow characteristics contributing to crash likelihood were quite different at different levels of severity. The PDO crashes were more likely to occur under congested traffic flow conditions with highly variable speed and frequent lane changes, while the KA and BC crashes were more likely to occur under less congested traffic flow conditions. High speed, coupled with a large speed difference between adjacent lanes under uncongested traffic conditions, was found to increase the likelihood of severe crashes (KA). This study applied the 20-fold cross-validation method to estimate the prediction performance of the developed models. The validation results show that the model¡¯s crash prediction performance at each severity level was satisfactory. The findings of this study can be used to predict the probabilities of crash at different severity levels, which is valuable knowledge in the pursuit of reducing the risk of severe crashes through the use of dynamic safety management systems on freeways.
  Authors: Xu, Chengcheng; Tarko, Andrew P.; Wang, Wei; Liu, Pan; Bai, Lu
  Authors: Xu, Chengcheng; Tarko, Andrew P.; Wang, Wei; Liu, Pan; Bai, Lu
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1715
• Travelers’ Preferences in Multimodal Networks: Design and Results of a Comprehensive Series of Choice Experiments
  Abstract: In this paper, we develop and apply a series of SP experiments to estimate a comprehensive multimodal, multi-stage travel choice model. In total, four experiments are designed focusing on particular multimodal (including P+R) and public-transport choices for trips of varying distance. A representative national sample (N = 2.746) of individuals from the Netherlands participated in the experiments through an online questionnaire. The data pooled across experiments are used to estimate the model in a scaled mixed multinomial logit framework. In this way, valuations of time, costs and service-quality attributes could be estimated on a relatively high level of detail concerning modes and trip stages. The estimation results can be used to specify link costs functions in multimodal network models for network analysis and route planning.
  Authors: Arentze, Theo A.; Molin, Eric
  Authors: Arentze, Theo A.; Molin, Eric
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-1310
• A Meta-Analysis of the Value of Travel Time Savings Incorporating GDP Per Capita: Evidence from Japanese Passenger Travels
  Abstract: This paper conducts a meta-analysis of the value of travel time savings (VTTS) in Japan. The meta-analysis is based on 261 VTTS estimated from 68 peer-reviewed papers on travel behavior in Japan between 1979 and 2003. First, the basic characteristics of VTTS are analyzed on the basis of purpose of travel, weekday or weekend travel, type of data, urban or inter-urban travel, and attributes of travel. Regression analyses are then conducted on all VTTS estimates, together with those of urban travel and inter-urban travel. Our analysis reveals that the VTTS estimated using the stated preference data are lower than those estimated with revealed preference data: (1) the VTTS of business travel is higher than that of home-to-school, private, and leisure travel and (2) the VTTS of access/egress time, wait time, and transfer time are higher than that of in-vehicle time. We also show that the VTTS of inter-urban travel is higher than that of urban travel. In addition, the VTTS elasticity of GDP per capita is estimated to be 0.55.
  Authors: Kato, Hironori; Tanishita, Masayoshi; Abe, Ryosuke
  Authors: Kato, Hironori; Tanishita, Masayoshi; Abe, Ryosuke
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1502
• Surrogate Safety Measure for Simulation-Based Conflict Study
  Abstract: This paper proposes a surrogate measure named Aggregated Crash Propensity Index (ACPI) for simulation-based conflict studies. A Probabilistic model named Crash Propensity Model (CPM) is developed to determine the crash probability of simulated conflicts, by introducing the distributions of reaction time and maximum braking rates. This CPM is able to generate ACPI for three different types: crossing, rear-end and lane change. A field validation effort is conducted by simulating three major arterials (twelve intersections) in simulation package (VISSIM). Surrogate Safety Assessment Model (SSAM) is utilized to extract useful conflict data as the entry into CPM model to get ACPI. The Spearman rank tests indicate that ACPI is able to identify the relative safety among traffic facilities/treatments. Notably, ACPI outperforms the Highway Safety Manual (HSM) procedures in both correlation and rank tests. Both linear and non-linear regression models are well fitted for ACPI and real crash frequency, suggesting its potential to be directly linked to real crash.
  Authors: Wang, Chen; Stamatiadis, Nikiforos
  Authors: Wang, Chen; Stamatiadis, Nikiforos
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1512
• Hysteresis and Urban Rail
  Abstract: Problem + research strategy: Cities are endowed with and accumulate natural and constructed assets based on their unique histories, which in turn define the choice set of the present. But, common practice is that current behavior can be described without reference to past circumstances. This work departs from that practice by examining the effects of historical urban rail on current residential location and travel behavior, from the era of horsecars and streetcars to the present in Boston. It uses aggregate spatial data, with controls for possible endogeneity over these long time frames to explore the hysteretical effects of past access to rail—the extent to which the urban system retains the impacts of rail even when it no longer exists. Findings: Current density and travel behavior are measurably influenced by past access to rail. These findings are robust to a series of alternate causal, functional, and spatial specifications. The built environment and demographic patterns are found to be the strongest mechanisms for these persistent effects. Past access to rail has shaped the city, and that shape has, in turn, affected travel behavior. For density and auto ownership there is an additional measurable effect of past access unexplained by the built environment or demographic patterns. This legacy is plausibly explained by cultural effects—mnemonics—due to personal history or behavioral norms. Takeaway for practice: This research shows that past rail access continues to reverberate in current residential location and travel behavior. These findings of quasi-irreversability add to an understanding of the long-term impacts of rail infrastructure, and imply a need to consider how policy decisions will influence the city's future choice set.
  Authors: Block-Schachter, David; Zhao, Jinhua
  Authors: Block-Schachter, David; Zhao, Jinhua
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1575
• Transportation Applications for Mobile Lidar Scanning:State-of-the-Practice Questionnaire
  Abstract: The relatively recent emergence of mobile Light Detection and Ranging (LIDAR) technologies as a potentially transformative tool for numerous transportation engineering applications coupled with a lack of existing standards has resulted in the need for an improved understanding of how this technology is currently being implemented, and what challenges are limiting its adoption. To that end, a questionnaire was administered to State Departments of Transportation (DOTs) to document and evaluate the state-of-the-practice regarding mobile LIDAR in transportation applications. Representatives from each of the 50 U.S. states and 6 additional transportation agencies completed the questionnaire, for a total of 74 responses. A second service provider questionnaire was completed by 14 companies experienced with mobile LIDAR services. Interestingly, it was determined that more DOTs have used mobile rather than airborne LIDAR services in the last year, even though mobile scanning is a less established technology. Additionally, the results showed that DOTs perceive cost to be one of the most significant challenges to the adoption of mobile LIDAR, indicating that more evidence and education are required regarding benefit to cost comparisons of the technology. The questionnaire also revealed current struggles as DOTs transition from two- to three-dimensional workflows and modeling. These questionnaires established a technology adoption baseline that can be used to measure future progress and provide the foundation for national guidelines currently under development.
  Authors: Hurwitz, David S.; Tuss, Halston; Olsen, Michael James; Roe, Gene; Knodler, Michael A.
  Authors: Hurwitz, David S.; Tuss, Halston; Olsen, Michael James; Roe, Gene; Knodler, Michael A.
  Year: 2013
  Document Type: Paper
  Subject: Construction; Data and Information Technology; Design
  Session: 582
  Paper Number: 13-1606
• Urban-Rural Difference of Gasoline Price Effects on Traffic Safety
  Abstract: A large literature base has found that economic factors have important effects on traffic crashes. A small but growing branch of literature also examines the role of gasoline prices in the occurrence of traffic crashes. However, no studies have investigated the possible difference of these effects between urban and rural areas. In this study, we used the monthly traffic crash data from 1998–2007 at the county level in Minnesota to investigate the possibly different effects gasoline prices may have on traffic crashes per million vehicle miles traveled in urban versus rural areas. The results indicate that gasoline price effects on total crashes, property-damage-only crashes, and injury crashes are stronger in rural areas than in urban areas. Gasoline prices also significantly affect fatal crashes in both urban and rural areas; however, the difference is not significant. The results concerning the differences between urban and rural areas have important policy implications for traffic safety planners and decision makers.
  Authors: Chi, Guangqing; Quddus, Mohammed A.; Huang, Arthur; Levinson, David M.
  Authors: Chi, Guangqing; Quddus, Mohammed A.; Huang, Arthur; Levinson, David M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1688
• Analysis of Factors Affecting Winter Collision Severity
  Abstract: This paper presents the results of an analysis aiming at identifying the main injury severity factors associated with road collisions that occur during snowstorms, including traffic conditions, road geometry and environment, pavement surface conditions as well as vehicle and driver characteristics. A multilevel multinomial logit model is introduced for capturing the hierarchical nature of the collision data between individual collisions and the vehicles and persons involved. Different from past studies, the modeling effort focuses on the collisions that occurred over snowstorms so that the effect of weather related factors are not masked due to the imbalance of data sample between collisions occurred under normal conditions and those under snowstorms. This approach is also necessary for ensuring that the incremental effect of different weather severity, as well as winter road maintenance operations, could be captured. Collisions occurred on a number of highway routes from the province of Ontario, Canada, over six winter seasons (2000-2006), were selected for this analysis. It was found that factors related to drivers (age, sex, condition), road characteristics (number of lanes, speed limit, road surface conditions), vehicle type, position in vehicle, use of safety belt, and traffic volume have statistically significant effects on collision severity outcome. In general, the modeling results indicate that good road surface conditions, high traffic volume, young and male drivers and new vehicles are associated with reduced injury severity levels. Our analysis, however, did not confirm the main finding from literature, that is, severer weather, such as higher precipitation intensity and wind speed, is associated with lesser collision severity.
  Authors: Usman, Taimur; Fu, Liping; Miranda-Moreno, Luis Fernando
  Authors: Usman, Taimur; Fu, Liping; Miranda-Moreno, Luis Fernando
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1669
• On the commonly accepted assumptions regarding observed motor vehicle crash counts at transport system locations
  Abstract: Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.)The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.
  Authors: Washington, Simon; Haque, Md. Mazharul
  Authors: Washington, Simon; Haque, Md. Mazharul
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 433
  Paper Number: 13-1841
• Urban Setting and Transportation Modes Repositories: Multilevel Mixture Model Specification
  Abstract: The overwhelming number of studies on the relationship between travel and the urban environment have typically examined whether density, mixed land use and other morphological and functional characteristics of neighbourhoods induce individuals to use more environmentally friendly modes of transportation and travel less distance. To contribute to this already substantial accumulation of knowledge, this study will focus on the relationship between urban environment and the possession of different means of transportation, motivated by the consideration that the acquisition of transportation modes precedes their actual use in the context of daily activity-travel patterns. The analysis is based on the 2009 Dutch National Travel Survey, involving 65535 respondents, who reported their possession of different transportation modes. First, descriptive analyses are performed, followed by the estimation of best subset binary probit models and a multi-level mixture model. Congruent with previous findings about the use of transportation modes, both the results of the descriptive and the formal modelling analyses strongly indicate the existence of a weak interaction between urban density and the (non-) possession of in particular the car. However, results at the same time suggest the lack of any strong relationship between urban setting and transportation modes repositories. Implications of these research findings are discussed.
  Authors: Rasouli, Soora; Timmermans, Harry J.P.
  Authors: Rasouli, Soora; Timmermans, Harry J.P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1940
• Phased Decisions Under Multiple Source of Uncertainty: Analysis of Multimodal Choice Behavior
  Abstract: Most previous research on route choice under uncertainty has examined simple single choices. To contribute and expand to this stream of research, the present study analyzes choice behaviour in phased decisions using the choice of multi-modal transportations chains as an example. An experimental design is constructed in which respondents first have to choose between two bus line/route alternatives, which vary in terms of travel times and associated uncertainty in these travel times, and then between two train lines/routes which vary in terms of the same attributes in the context of an appointment for an interview. Results indicate that individuals exhibit risk-avoiding behaviour. To the extent they take risk, it tend to concentrate at the first phase of the two-phased decision process. Except for age, the effects of socio-demographic variables are not significant. Limitations of the present study and critical considerations for any future work on this topic are discussed in completing the paper.
  Authors: Rasouli, Soora; Timmermans, Harry J.P.
  Authors: Rasouli, Soora; Timmermans, Harry J.P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-1941
• Exploring Commuting Flexibility with GPS Data: Case Study in Beijing
  Abstract: This paper explores the Intra-personal day-to-day variability and flexibility of commuting behavior. Commuting behavior has been widely investigated based on questionnaire data from trip and activity dairy surveys. There has been very limited research focused on day-to-day variations in commuting behavior. The rapid development of location-based technologies and ICTs brings new opportunities for better insight into commuting with tracking data which has higher space-time accuracy and is easier to collect long-term data. In transitional urban China, the residents¡¯ commuting behavior, including travel distance, travel duration, travel mode and route choice varies greatly, and patterns could be rather complex. To better understand complex patterns of commuting behavior, this paper uses the concept of commuting flexibility. Four dimensions are defined on the basis of existing literatures and actual situation, and are measured by the GPS data for day-to-day travel. Data for this study are drawn from a 2010 Beijing activity-travel survey, including 100 residents in two selected suburban communities. We combine 7 days GPS tracking data and activity-travel dairy to explore residents¡¯ commuting flexibility and commuting patterns. The time geography framework is used to visualize weekly commuting patterns and show four dimensions of commuting flexibility synthetically. The paper tries to explain the commuting flexibility from the perspectives of institution, planning, policy and culture.
  Authors: Shen, Yue; Chai, Yanwei
  Authors: Shen, Yue; Chai, Yanwei
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-1951
• Improving Accuracy of Bluetooth-Based Travel Time Estimation Using Low-Level Sensor Data
  Abstract: Bluetooth sensors have a large detection zone compared to other static Vehicle Re-Identification Systems (VRIS). Although larger detection zone increases the probability of detecting a Bluetooth-enabled device in a fast moving vehicle, but it increases the probability of multiple detection-events triggered by a single device. This could lead to location ambiguity and reduces the accuracy of travel time estimation. Therefore, the accuracy of travel time estimations by Bluetooth Technology (BT) depends upon how location ambiguity is handled by the estimation method. The issue of multiple detection-events in the context of travel time estimation by BT has been considered by various researchers. However, the treatment of this issue has remained simplistic so far. Most previous studies simply used the first detection-event (Enter-Enter) as the best estimate. No systematic analysis for exploring the most accurate method of estimating travel time using multiple detection-events has been conducted. In this study different aspects of BT detection zone including the size and its impacts on the accuracy of travel time estimation are discussed. Moreover, four alternative methods are applied namely, Enter-Enter, Leave-Leave, Peak-Peak and Combined to estimate travel time. These methods are developed based upon various technical considerations related to multiple detection-events. A controlled field experiment is conducted to evaluate the accuracy of alternative methods through comparison with the ground truth travel-time data measured by GPS. The Results show that the accuracy of Combined and Peak-Peak methods are higher than others and employment of first detection-event does not necessarily yield the best travel time estimation.
  Authors: Namaki Araghi, Bahar; Tørholm Christensen, Lars; Krishnan, Rajesh; Hammershøj Olesen, Jonas; Lahrmann, Harry
  Authors: Namaki Araghi, Bahar; Tørholm Christensen, Lars; Krishnan, Rajesh; Hammershøj Olesen, Jonas; Lahrmann, Harry
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-1922
• Investigating Changes in Willingness to Pay for Managed Lane Systems: Quasi-Panel Approach
  Abstract: This paper investigates the hypothesis that the willingness-to-pay for managed lanes changes through time in the aftermath of opening and operating a facility. Using a quasi-panel of stated preference surveys, we found that the estimates of the value of travel time savings are higher two years after the opening and operation of managed lanes in both regular and urgent situations. These results provide an indication of a lingering perception of the inherent value offered by managed lanes becomes more evident after the lanes have been opened and used.
  Authors: Patil, Sunil; Concas, Sisinnio; Burris, Mark W.; Devarasetty, Prem Chand
  Authors: Patil, Sunil; Concas, Sisinnio; Burris, Mark W.; Devarasetty, Prem Chand
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-2052
• Activity Fragmentation, ICT, and Travel: Unraveling Interrelationships with Structural Equation Models
  Abstract: A substantial number of studies have addressed the relationship between Information and Communication Technologies (ICT), daily activities (here, paid work) and travel. Most studies have been primary concerned with direct effects of ICT on activities and travel. The aim of this study is to gain more insight into the relationship between ICT and travel behavior by using fragmentation as an intermediate concept to investigate how ICT influence travel behavior. The concept of fragmentation relates to how activities are reorganized temporally and spatially linked to ICT use. The causality of ICT, activity fragmentation and travel relationships remains to date unclear. We examine different causalities between ICT use, fragmentation and frequency of travel, based on a two-day communication-activity-travel data collected in The Netherlands. Using three different specifications, structural equation models (SEM) are applied to investigate the likely directions of the relationships. The results show that the causal associations between fragmentation ICT and travel are far from simple. ICT mediate the participation in non-work activities and can both substitute and complement the number of trips depending on the traveller’s attributes and type of ICT devices. More work fragmentation seems to limit the ability to travel for non-work purposes compared to work trips which is less elastic. ICT and fragmentation appear to have a reciprocal relationship with mobile ICT use influencing fragmentation while sedentary communications are more determined by the degree of fragmentation.
  Authors: Alexander, Bayarma; Ben-Elia, Eran; Ettema, Dick
  Authors: Alexander, Bayarma; Ben-Elia, Eran; Ettema, Dick
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 791
  Paper Number: 13-2057
• Developing Cost Estimation Models for Road Rehabilitation and Reconstruction
  Abstract: The average unit costs of road works vary substantially between countries, and even between projects in the same country, due to a number of factors. In this paper an effort is made to develop prediction models for the unit costs of road works that could be applied for a wide range of conditions in different countries.A specialized dataset was used, which was generated under a World Bank study that included road works contracts from 14 countries in Europe and Central Asia (ECA). Two techniques were used for model development: multiple regression analysis and artificial neural networks. As the major problem found with the data set was missing or incomplete data, classification trees were used as an intermediate step to evaluate the correctness of the selected parameters.Three models were developed using regression analysis, two for the unit cost of asphalt concrete and one for the cost per km of rehabilitation and reconstruction works. The models include as independent variables the price of diesel fuel, country Gross National Income, World Governance Index, Transparency International Corruption Perception Index, percent of local bidders participating in the tender, and climate conditions. The analysis using classification trees confirmed the appropriateness of the variables selected in the regression analysis. The models developed using artificial neural networks were superior compared to the regression models, using mostly the same parameters.The resulting models could be particularly useful at the strategic level, for planning and optimization of works on road networks in ECA countries.
  Authors: Cirilovic, Jelena; Vajdic, Nevena; Mladenovic, Goran; Queiroz, Cesar
  Authors: Cirilovic, Jelena; Vajdic, Nevena; Mladenovic, Goran; Queiroz, Cesar
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-2037
• Modeling Large-Truck Safety Using Logistic Regression Models
  Abstract: Statistics shows that crashes involving large trucks are generally more severe than those involving other vehicles due to the size, weight, and speed differential between trucks and other vehicles. Given the critical position of trucking in the process of economic recovery and growth, it is urgent to improve truck safety and mitigate any negative impacts to non-truck vehicles. Statistical models have been used universally to identify the contributing factors to crash severities and estimate injury probabilities. These different methodologies, albeit addressing different issues, may provide mixed results and the estimate accuracy may vary.The primary objective of this research is to investigate the effects of key determents to crash severities involving large trucks and to explore the relationship between them. The secondary objective is to provide insight on statistical applications by evaluating three logistic regression models: multinomial logistic (MNL), partial proportional odds (PPO), and mixed logistic (ML) models. The model results show that the majority of the coefficient estimates are consistent across the models studied. A few exceptions include young drivers and the use of safety constraints, which are not statistically significant in the ML model. The goodness-of-fit and model predictive power indicates that the PPO model produced the results that more closely resembled observations.
  Authors: Qin, Xiao; Wang, Kai; Cutler, Chase E.
  Authors: Qin, Xiao; Wang, Kai; Cutler, Chase E.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-2067
• Analyzing Crash Severity Based on Vehicle Damage and Occupant Injuries
  Abstract: In recent years, the reduction of injury crashes has been heralded as a great success. Improvements in federally mandated safety standards and advancements made by automotive industries to enhance the vehicle safety can be partially credited with the decline. Now, the national strategy on highway safety is to move “Toward Zero Deaths”. From this “Vision Zero” perspective, one of the appropriate strategies is to manage kinetic energy in crashes and collisions, i.e. minimizing the energy transferred to the human body, because the kinetic energy is responsible for occupant injuries and fatalities. Vehicle damage conditions are an unbiased indicator of kinetic energy in collisions while injury severities are the ultimate measure of the occupant risks. In this study, the vehicle damage and occupant injury models were developed for single-vehicle (SV) and multiple-vehicle (MV) crashes, respectively. The results of these models provide a complete view of the crash severity determinants and how they affect the occupant injuries and vehicle damage. Some factors have consistent impact across both injury severities and vehicle damage, while others are contradictory. Combining information from both occupants and vehicles is valuable for an impartial evaluation of specific components in highway design and an accurate assessment of the impacts of occupant characteristics, driver behavior, and errors on the resultant bodily injuries.
  Authors: Qin, Xiao; Wang, Kai; Cutler, Chase E.
  Authors: Qin, Xiao; Wang, Kai; Cutler, Chase E.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-2072
• Agent-Based Modeling of Intergovernmental Decision Making: How Institutional Rules Generate Basins of Attraction in Funding Transportation Projects
  Abstract: A Pattern-Oriented, Agent Based Model (ABM) of an intergovernmental network is presented to demonstrate an application of complex systems and computational modeling in real world transportation policy implementation processes. This ABM simulates the dynamics of intergovernmental decision making that is deployed for transportation project prioritization processes. The ABM simulates baseline and alternate intergovernmental institutional rule structures and assesses their impacts on financial investment flows from federal to state, regional and local scale governments. The current version of the ABM is limited to simulating roadway projects in the state of Vermont that are primarily funded through US Surface Transportation Program and Interstate Maintenance Program. Multiple focus groups, individual interviews, and analysis of federal, state and regional scale transportation project and program data was used to calibrate this ABM. In particular, this ABM demonstrates how institutional rules set by federal, state and regional government agencies generate “basins of attraction” in funding roadway projects. The results from experimental simulations are presented to test system-wide effects of alternate institutional designs on the differential emergence of roadway project prioritization patterns and funding allocations across regions and local towns.
  Authors: Zia, Asim; Koliba, Christopher
  Authors: Zia, Asim; Koliba, Christopher
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-2153
• Transit Smart Card Data Mining for Passenger Origin Information Extraction
  Abstract: The Automated Fare Collection (AFC) system, also known as the transit smart card system, has gained more and more popularity among transit agencies worldwide. Compared with the conventional manual fare collection system, an AFC system has its inherent advantages in low labor cost and high efficiency for fare collection and transaction data archival. Although it is possible to collect highly valuable data from transit SC transactions, substantial efforts and methodologies are needed for extracting such data because most AFC systems are not initially designed for data collection. This is especially true for Beijing’s AFC system, where a passenger’s boarding stop (origin) on a flat-rate bus is not recorded on the check-in scan. To extract passengers’ origin data from recorded SC transaction information, a Markov chain based Bayesian decision tree algorithm is developed in this study. Using the time invariance property of Markov chain, the algorithm is further optimized and simplified to reduce its computational complexity to linear. This algorithm is verified with transit vehicles equipped with GPS data loggers. Our verification results demonstrated that the proposed algorithm is effective and efficient in extracting transit passengers’ origin information from SC transactions with a relatively high accuracy. Such transit origin data are highly valuable for transit system planning and route optimization.
  Authors: Ma, Xiaolei; Wang, Yinhai; Chen, Feng; Liu, Jianfeng
  Authors: Ma, Xiaolei; Wang, Yinhai; Chen, Feng; Liu, Jianfeng
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 530
  Paper Number: 13-2156
• Accommodating Underlying Proenvironmental Attitudes in a Rail Travel Context: Application of a Latent Variable Latent Class Specification
  Abstract: Using data from a stated preference survey conducted in the United Kingdom, we show how the willingness to reduce reduce greenhouse gas emissions and accept longer travel time varies strongly as a function of underlying attitudes towards the environment. We specify a latent class structure that allocates respondents to two classes with substantially different valuations of greenhouse gas emissions, and show how the allocation of a given respondent to either class is a function of underlying attitudes that also drive the answers to a number of attitudinal questions. We also show how these underlying attitudes are a function of a number of socio-demographic characteristics, with female respondents, older respondents, and respondents with a university degree having a stronger pro-environmental attitude, with the opposite applying to respondents with regular car access.
  Authors: Hess, Stephane; Shires, Jeremy; Jopson, Ann
  Authors: Hess, Stephane; Shires, Jeremy; Jopson, Ann
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-2241
• Tablet and Web-Based Regional Airport Travel Survey with Synchronized Bluetooth Traffic Data Collection
  Abstract: This paper provides an overview of the comprehensive data collection effort completed at two Phoenix airports in order to update and recalibrate ground-access travel sub-models. Central to this effort was an advanced, tablet-based air passenger survey that used mapping software to collect air passenger trip diaries with detailed origin-destination location information. This paper discusses the airport survey design, sampling plan, data expansion plan, and survey instruments as well as Bluetooth® Automatic Wireless Address Matching origin-destination data and other traffic data collection. It discusses challenges faced and lessons learned. The Maricopa Association of Governments (MAG), the metropolitan planning organization for the Phoenix metropolitan area, carried out the comprehensive airport data collection effort in collaboration with the City of Phoenix, City of Mesa, Phoenix Sky Harbor International Airport, and Phoenix-Mesa Gateway Airport.
  Authors: Gorton, Michael; Livshits, Vladimir; Kuppam, Arun R.; Brown, Ted; Tierney, Kevin; DeBoer, Kathy
  Authors: Gorton, Michael; Livshits, Vladimir; Kuppam, Arun R.; Brown, Ted; Tierney, Kevin; DeBoer, Kathy
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-2246
• Effect of Driving Restrictions on Travel Behavior in Beijing
  Abstract: This article measures the effect of Beijing’s driving restrictions on individual travel behavior using 2010 Beijing Household Travel Survey data. Driving restrictions decrease the auto use, however, with the effect lower than expectation. Evidence from trip frequency indicates that the adjustment in travel behaviors varies across individuals: for example, female, high-income drivers who live in the south of the Beijing central city tend to decrease auto use more facing restrictions. Drivers also make inter-temporal adjustments in trip making, especially within a 3-day time window. We also provide evidence of the uneven restrictions, that is, high traffic flow in the 4&9 restricted days, as well as how non-drivers decrease their trip frequency in such days.
  Authors: Gu, Yizhen; Deakin, Elizabeth; Long, Ying
  Authors: Gu, Yizhen; Deakin, Elizabeth; Long, Ying
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-2352
• Urban Travel Demand Analysis for Austin, Texas, Using Location-Based Social Networking Data
  Abstract: The location-based social networking (LBSN) is a location-sensitive service interactively carried out by users with mobile devices, such as smart phones, to “check-in” with the “venues” reflecting their daily activities. With its increase popularity and sophistication, the location-based social networking (LBSN) data have emerged as a new data source for studying urban travel demand. Comparing with traditional Origin-Destination (O-D) estimation method such as survey based or traffic count based methods, LBSN data has the potential to provide O-D estimation with much higher temporal resolution at much lower cost. In this paper, the Foursquare LBSN data was used to analyze the O-D demand for the urban area near Austin, Texas, USA. A gravity model with two-regime friction factor functions is proposed to estimate the O-D matrix. The proposed methods are calibrated and evaluated against the ground truth O-D data from CAMPO (Capital Area Metropolitan Planning Organization). The results illustrate the promising potential of using LBSN data for urban travel demand analysis and monitoring.
  Authors: Jin, Jing; Yang, Fan; Cebelak, Meredith; Ran, Bin; Walton, C. Michael
  Authors: Jin, Jing; Yang, Fan; Cebelak, Meredith; Ran, Bin; Walton, C. Michael
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 299
  Paper Number: 13-2374
• Effects of Household Structure and Accessibility on Travel
  Abstract: The concept of accessibility has been widely used in the transportation field, commonly to evaluate transportation planning options. The fundamental hypothesis of those accessibility-related studies could be “greater accessibility leads to more travel”. However, several studies showed inconsistent results with the common hypothesis, that is, accessibility is independent of trip/tour frequency. In addition, empirical aggregate urban modeling applications commonly produce either non-significant or negative (wrong sign) relationships between accessibility and trip/tour frequency. For this reason, many practitioners rarely incorporate a measure of accessibility into trip/tour generation models for induced demand consideration. In this context, this study examined the effect of accessibility in urban and suburban residence on the maintenance and discretionary activity tour frequencies of the elderly and the non-elderly using household travel survey data collected in the Seoul Metropolitan Area, Korea. The major finding of this study is that higher density of land use and better quality of transportation service do not always lead to more tours due to the presence of intra-household interactions, trip chaining, and different travel needs by activity type. This finding implies that accessibility-related studies should not unquestioningly accept the common hypothesis when they apply accessibility measures to evaluate their transportation planning options or incorporate them into their trip/tour generation models.
  Authors: Seo, Sang-Eon; Ohmori, Nobuaki; Harata, Noboru
  Authors: Seo, Sang-Eon; Ohmori, Nobuaki; Harata, Noboru
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-1873
• Modeling Traffic Accidents on Auckland Motorway, New Zealand
  Abstract: This paper investigates motorway safety by developing accident prediction models that link accident frequencies to their non-behavioural contributing factors, including traffic conditions, geometric and operational characteristics of road, and weather conditions. The study used a sample of accidents occurred from 2004 through 2010 on a 74 km long section of Auckland motorway. A number of accident prediction models were developed and assessed for their predictive ability using negative binomial regression models under three categories: first for the whole of the motorway, second for rural and urban motorway segments separately and third for motorway segments without ramp, with on-ramp and with off-ramp separately. The results uncovered the safety impacts of different non-behavioural contributing factors, in which segment length, AADT per lane and the number of lanes always have the most profound effects on accident frequency. The findings make the recommendation of effective countermeasures on motorway safety to be possible.
  Authors: Chngye, Pan; Ranjitkar, Prakash
  Authors: Chngye, Pan; Ranjitkar, Prakash
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-1976
• Methodology for Determining Traffic Accident Risk Zones
  Abstract: In Costa Rica, the traffic accident database is still under development. Due to the limited quantity of information it is very difficult for the DOT to the accurately locate the road sections with significant concentration of accidents, also known as “blackspots”. The National Laboratory of Materials and Structural Models of the University of Costa Rica (LanammeUCR) has developed a methodology that initially assesses the potential risk of accidents associated with a combination of four different parameters related to road infrastructure and the environment. The study was performed in four of the Country’s main highways, for a study length of over 1,000 km of roads. The parameters considered in the methodology were: pavement friction, retro-reflectivity of the road marking, geometrical and topographical alignment of the roadway and climatic factors. The experimental parameters associated with each category were measured directly based on NDT testing. The climatic factors were based on current and historical weather station information. The proposed methodology consists of a combination of values for each individual parameter, which finally result in a susceptibility profile for the road, which is related to the risk that an accident will occur. All of the data was plotted in geo-referenced maps to be available for road users and the government. Finally, the results were correlated with accident data to verify for the sensitivity of the method.
  Authors: Aguiar-Moya, José Pablo; Barrantes-Jimenez, Roy; Sanabria, Jairo; Loria-Salazar, Luis
  Authors: Aguiar-Moya, José Pablo; Barrantes-Jimenez, Roy; Sanabria, Jairo; Loria-Salazar, Luis
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-2286
• Verb-Based Text Mining of Road Crash Report
  Abstract: Traffic accident report is usually completed by police officers at the scene and contains important information on the cause and outcome of automobile accidents. However, a significant part of the report is stored in unstructured textual format. In the existing literature, there is only a handful of studies on extracting useful information from the crash report. In this research, we developed a verb-based text mining method. This method identifies and extracts the main verbs representing the vehicle actions in a sentence. Using those verbs, we are able to extract the sequence of events of the crash accident. The vehicle action entities are identified through using Natural Language Processing (NLP) techniques to identify both syntactic and semantic units in the text. The developed verb-based approach can effectively handle complex sentence structures such as clauses and conjunctive sentences. In the case study, we evaluated the proposed method using a total of 945 accidents records published by Missouri State Highway Patrol during the period from May 19, 2012 to June 27, 2012. The obtained results show that the extracted information is useful not only to crash classifications but also to help understand the causes of crashes.
  Authors: Gao, Lu; Wu, Hui
  Authors: Gao, Lu; Wu, Hui
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 433
  Paper Number: 13-2292
• Effect of Sun Glare on Traffic Accidents in Japan
  Abstract: This study aims to clarify effect of sun glare on traffic accident occurrence. Traffic accidents analyses were carried out to calculate the position of the sun relative to the first vehicle concerned (i.e., the vehicle most responsible for causing the accident) at the accident time and spot by using the traffic accident database of Chiba Prefecture. Daytime traffic accidents that occurred during fine weather were extracted for analysis. The traffic accident rate was found to increase when the viewing angle decreased to less than 90 degrees. Daytime traffic accidents during fine weather were extracted, and traffic accidents in which this viewing angle was less than 90 degrees were regarded as sun-glare-related ones, and all others were regarded as sun-glare-unrelated ones. Logistic regression analyses were carried out, with the viewing angle as the dependent variable and certain traffic accident data items as the independent variables. When the sun was in front of the first vehicle concerned, the accident rate was much higher for pedestrian accidents, bicycle accidents and accidents at intersection and slightly higher for right-turning accidents and accidents in winter. However, the tendency for vehicle drivers to be affected adversely by sun glare was not observed to increase with increases in vehicle speed. The sun glare tended to cause drivers to not see pedestrians and cyclists at signalized intersections. Traffic safety measures against such kinds of accidents are needed.
  Authors: Hagita, Kenji; Mori, Kenji
  Authors: Hagita, Kenji; Mori, Kenji
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-2388
• Hotspot Identification Under Limited Information: Combined Probabilistic and Fuzzy Cluster-Based Approach
  Abstract: Hot-Spot Identification (HSID) requires crash history information such as annual crash counts, their severities etc and details such as annual traffic exposure and geometric design details. The most recommended HSID method— Empirical Bayes utilizes at least crash history and traffic volume information to develop Safety Performance Function (SPF), which is used to compute expected number of crashes at a given site. However, in the absence of systematic data collection and maintenance, information about geometric design and traffic volume is not only difficult to obtain, but also demands significant resources. In such circumstances, only crash-count based (CCB) HSID techniques, such as Crash Frequency (CF) method, Fatal Crash Frequency (FCF) method and Equivalent Property Damage Only (EPDO) methods may only be adopted even with their known limitations. In this article, the authors suggested a new method of HSID, using disaggregate crash history information in crash severity model. Based on the probabilities of crash severities by the major contributing factors, expected numbers of severe and fatal crashes are calculated. These expected crash counts are used to classify locations into two fuzzy clusters— a) black-spots and b) white-spots using Fuzzy C-Means (FCM) algorithm. The identified hotspots are ranked based on their mean departure from core of the hotspot cluster. Site consistency, Method consistency and Total rank differences tests are used to compare the performance of the method with other CCB-HSID techniques. Results show the robustness of the proposed FCM method as it performs well in all consistency tests.
  Authors: Bandyopadhyaya, Ranja; Mitra, Sudeshna
  Authors: Bandyopadhyaya, Ranja; Mitra, Sudeshna
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-2379
• Analysis of Route Choice Using Private Probe Data Considering Heterogeneity in Familiarity to Origin-Destination Pairs
  Abstract: An exploratory analysis about the heterogeneity in familiarity to OD pairs is carried out. This analysis is based on the probe data collected by private vehicles in Toyota, Japan. The hypothesis test results show that route choice behavior changes relating to the familiarity to OD pairs. Two specifications of choice models are proposed to consider the effect of familiarity explicitly. The estimation results show that the models consider familiarity fit the data better, and suggest that trips between more familiar OD pairs have larger error variances and less sensitivity to explanation variables. The estimated models are applied to a specific choice situation, the prediction results show the potential biases introduced by not considering heterogeneity in familiarity to OD pairs.
  Authors: Li, Dawei; Miwa, Tomio; Morikawa, Takayuki
  Authors: Li, Dawei; Miwa, Tomio; Morikawa, Takayuki
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 299
  Paper Number: 13-2393
• Effects of Household Structure on Grocery Shopping Behavior of Elderly in South Korea
  Abstract: Traditionally, Koreans in their old age tend to reside with adult children and receive physical and psychological support from them. This feature may have positive effects on the quality of life for the elderly. However, recent official statistics show Korea¡¯s soaring elderly households residing without adult children, indicating a need to examine the effects of household structure on the elderly. In this context, first, this study explored the effects of household structure on elderly grocery shopping behavior with a focus on grocery shopping frequency, accompanying behavior, and enjoyment with grocery shopping activities by estimating full structural equation models. In addition, aggregate urban modeling applications on the relationship between accessibility and trip/tour frequency commonly produce either non-significant or negative associations which violate the basic economic theory, that is, lower travel cost leads to more travel. We conjectured that individuals¡¯ subjective satisfaction with activities could lead to such unreasonable results. Therefore, the other objective of this study is to identify the possible causes to lead the unreasonable relationship between accessibility and trip/tour frequency. First of all, a hypothesized single population model was statistically tested by estimating a full structural equation model. Second, the entire survey dataset was segmented into four comparison groups by four dichotomous segmentation variables. The results showed that co-residence with adult children and better family relationship significantly alleviate the difficulties of the elderly such as elderly physical mobility and residential accessibility to grocery shopping places, consequently improving grocery shopping enjoyment of the elderly and the quality of life.
  Authors: Seo, Sang-Eon; Ohmori, Nobuaki; Harata, Noboru
  Authors: Seo, Sang-Eon; Ohmori, Nobuaki; Harata, Noboru
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-2406
• Analysis of Factors Affecting Freeway Traffic Crash Frequency Under Different Light Conditions with Random Parameter Count Models
  Abstract: This research develops a random parameter count model of crash frequency on freeways with a speed limit of 110 km/h in Korea and performs a comparison between time periods (daytime, nighttime, twilight, and the whole 24 hour period). Data for crashes in 2007-2010, excluding vehicle factors such as engine overheating and malfunction in damping device and human factors such as drunk driving and dosing off at the wheel, was drawn from Korea freeway crash data. The results show several factors having random effects on crashes: traffic share of light vehicles, number of lanes, urban area, and foggy area. While some factors are statistically significant regardless of the time period (e.g., traffic share of light vehicles, number of lanes, urban area, frequent fog in area, and number of days with snowfall), some factors have statistical effects only during certain time periods (e.g., number of interchanges/junctions and number of bridges during daytime, traffic share of heavy vehicles during nighttime and the whole 24 hour period, and short tangent (<1,421 m) and number of crest vertical curves during twilight). The results indicate that the effect of roadway geometrics on crash frequency differs by time of day which can be used in driver information systems to supply different information to drivers about the road ahead based on time of day. For example, during daytime drivers need more information about upcoming interchanges/junctions. The results indicate that roadway design should try to avoid combining horizontal and sag vertical curves.
  Authors: Hong, Sungmin; Kim, Joon-Ki; Oh, Cheol; Ulfarsson, Gudmundur Freyr
  Authors: Hong, Sungmin; Kim, Joon-Ki; Oh, Cheol; Ulfarsson, Gudmundur Freyr
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-2397
• Evaluating Accuracy of New Algorithm for Extracting Vehicle Tracking Data from Videotaping
  Abstract: A methodology for tracking moving vehicles is presented that overcomes many of the practical limitations of current video taping applications many resulting from traffic and site conditions for the road segment being video-taped. The algorithm presented in this paper provides a sound inexpensive procedure for extracting vehicle tracking data with minimum video taping restrictions. This is achieved through a comprehensive filtering of videotaped images, removal of background distortions, reduced impact of image occlusion, identification and construction of blobs from pixel features, and an accurate link to fixed representative reference points inside of the video frame (Ground Control Points or GCP). The tracking algorithm has been applied to a sample of video-taped vehicle trajectories with parallel GPS geo-referenced information to investigated the effect of placement of GCP and video camera angle on error in vehicle tracking.The number of GCP and the deflection angle from the perpendicular camera sightline to the roadway have a significant effect on the accuracy of the detected vehicle trajectories. Slightly higher errors were noted for a small number of GCP. Accuracy in the tracking algorithm is important for the calibration and validation of microscopic traffic simulation models.
  Authors: Guido, Giuseppe Piero; Vitale, Alessandro; Saccomanno, Frank; Astarita, Vittorio; Giofrè, Vincenzo P.
  Authors: Guido, Giuseppe Piero; Vitale, Alessandro; Saccomanno, Frank; Astarita, Vittorio; Giofrè, Vincenzo P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-2475
• Toward GIS-Compliant Data Structures for Traffic and Transportation Models
  Abstract: In many traffic and transportation models, data structures used for input and output do not adhere to common data formats. Consequently, many different architectures are used concurrently with little or no relation to the geographic information systems that carry and provide these data. As a result, the exchange of data between traffic models is often cumbersome. To improve the usability of geo-information, this paper studies the establishment of a standard for the transport domain that aligns to an existing international standard for geo-information, i.e. CityGML (Geographical Markup Language for city and landscape models). The Open Geospatial Consortium (OGC) established this standard as a generic standard for 3D modelling of topographic features. In this paper we propose a standard for traffic and transport modelling in the form of a CityGML Application Domain Extension (ADE). First, we analyse the data requirements for traffic and transportation models and present a description of objects that are necessary to build the traffic infrastructure for traffic models. By comparing these data with the CityGML data model concepts, we show a strong semantic match between concepts required in the transport domain and CityGML. Consequently, defining a standard for input data in the transport domain that aligns to CityGML will make it possible to reuse geo-information that was acquired for other purposes. This paper also shows the possibilities to extend CityGML to support properties that are specific to the transport domain. Further research will focus on further detailing the CityGML ADE for Transport and testing it in traffic and transportation models
  Authors: Tamminga, Guus; van den Brink, Linda; Van Lint, Hans; Stoter, Jantien; Hoogendoorn, Serge
  Authors: Tamminga, Guus; van den Brink, Linda; Van Lint, Hans; Stoter, Jantien; Hoogendoorn, Serge
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 283
  Paper Number: 13-2455
• Cyber-ITS Framework for Massive Traffic Data Analysis Using Cyberinfrastructure
  Abstract: Traffic data is commonly collected from widely-deployed sensors in urban areas. This brings up a new research topic, data-driven intelligent transportation systems (ITS), which means to integrate heterogeneous traffic data from different kinds of sensors and apply it for ITS applications. This research, taking into consideration of significant increase in the amount of traffic data and the complexity of data analysis, focuses mainly on the challenge of solving data-intensive and computation-intensive problems. This paper proposes a Cyber-ITS framework to perform data analysis on Cyber-Infrastructure (CI) in the context of ITS, as a solution to the problems. The Cyber-ITS framework is based on a core component, computational intensity, which allows the traffic data analysis to efficiently allocate and utilize CI. The techniques of the framework include data representation, domain decomposition, resource allocation, and parallel processing. All these techniques are based on data-driven and application-oriented models, and are organized as a component-and-workflow-based model in order to achieve technical interoperability and data reusability for various data-driven ITS applications. A case study of the Cyber-ITS framework is presented later based on a traffic state estimation application that uses the fusion of massive Sydney Coordinated Adaptive Traffic System (SCATS) data and GPS data. The results prove that the Cyber-ITS-based implementation can achieve a high accuracy rate of traffic state estimation, and provide a significant computational speedup for the data fusion by parallel computing.
  Authors: Xia, Yingjie; Hu, Jia; Fontaine, Michael Daniel
  Authors: Xia, Yingjie; Hu, Jia; Fontaine, Michael Daniel
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 283
  Paper Number: 13-2419
• Modeling Frequency of Traffic Conflicts at Signalized Intersections Using Generalized Linear Regression Models
  Abstract: The primary objective of this study was to identify the potential of using conflict prediction models to predict the frequency of traffic conflicts at signalized intersections. The opposing left-turn conflicts were selected for the development of conflict prediction models. Using data collected at thirty approaches at twenty signalized intersections where the permitted left-turn phases were used, the underlying distributions of the conflict frequency for different volume regimes in different time intervals were examined. It was found that the conflict frequency generally followed a negative binominal distribution. Different conflict prediction models were developed, including a linear regression model, an overall negative binomial model, and separate models developed for four traffic scenarios which were defined based on the volume to capacity ratio of the conflicting traffic flows. The prediction performance of different models was compared. It was found that the linear regression model was not appropriate for modeling the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Thus, the effects of conflicting traffic volumes on conflict frequency were different in different traffic conditions. The generalized linear regression models developed for different traffic scenarios provided the best estimates for the field measured conflicts.
  Authors: Zhang, Xin; Liu, Pan
  Authors: Zhang, Xin; Liu, Pan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-2427
• Reliable Game Model for Network Violator Interception Problem
  Abstract: This paper focuses on planning interceptor locations in a general transportation network to maximize the expected benefits from catching violators mixing in public traveler flow. We use travel distance of violators before intercepted and innocent public traveler flow encountered by violators to define the expected benefit by setting interceptors along a specific route. Two reliability-related characteristics are also integrated into the planning model to make it more practical. One is each interceptor (maybe a sensor, a checkpoint or something else) have a failure probability. Different failure scenarios may incur different layout decision of interceptors and investigation of failure can lead to a more reliable solution. The other is there is a ¡°game¡± between interceptor planner and violators. We assume violators will adjust their route choices according to the interceptor layout decided by planner. Logit choice model is used to account for the route adjustment conducted by violators. Consequently, a non-linear non-convex binary integer programming model is presented. We develop a Simulated Annealing (SA) algorithm to solve it. A set of numerical experiments are conducted to illustrate the computational efficiency of the proposed algorithm. Further, we analyze the sensitivity of disruption probability of interceptors to optimal objective function values and discuss how to determine the values of parameters in violator route choice model.
  Authors: An, Shi; Cui, Jianxun; Wang, Jian
  Authors: An, Shi; Cui, Jianxun; Wang, Jian
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-2431
• A Spatiotemporal Data Warehouse for Vehicle Supervision: A Grid Time-Indexed Cube Approach
  Abstract: The large amounts of spatiotemporal data generated by vehicle supervision systems cannot be efficiently managed by ordinary databases, mainly due to long query responses. To overcome the limitations of ordinary databases, this paper proposes a new approach known as the Grid-Time indexed Cube (GT-Cube), which is a spatial grid-indexed, adaptive grid-based and trajectory-supported warehouse for spatiotemporal data. The GT-Cube partitions an embedded space-time into a set of size-fixed grids to form a cube that continues to grow throughout a constant time interval. Each grid is assigned an ID composed of its coordinates and start time, and an aggregated value for each grid is stored in the grid records regardless of the temporal length of the queries. Additionally, the basic grid structure of the GT-Cube remains unchanged at each time interval. Instead, this method refines the grid in a selected region to handle data skew by adaptively partitioning the grid into sub-grids. After conducting extensive performance studies based on spatiotemporal data from the main vehicle supervision system of Guangdong province, we observed that the GT-Cube achieved higher query performance than ordinary data storage technologies under various operational conditions, was easily applicable in practice, and demonstrated compatibility with traditional databases.
  Authors: Hu, Ji-hua; Cheng, Zhi-feng; Zhan, Cheng-zhi; Tang, Wei
  Authors: Hu, Ji-hua; Cheng, Zhi-feng; Zhan, Cheng-zhi; Tang, Wei
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 793
  Paper Number: 13-2458
• Uncertainty in Predicted Sequences of Activity-Travel Episodes: Measurement and Analysis
  Abstract: Application of uncertainty analysis requires appropriate statistics that capture the degree of uncertainty in model forecasts. Prediction of activity-based models of travel demand relates to (i) aggregate performance indicators; (ii) origin-destination tables and corresponding traffic flows, (iii) individual space-time trajectories and (iv) the sequence of activities that are conducted during the day. Realising that measures aiming at quantifying uncertainty in such multi-dimensional activity-travel sequence patterns have not been developed in transportation research, the aim of this paper is to propose an approach to measure uncertainty in predicted activity-travel sequences. The proposed method involves generating predicted activity-travel patterns for different model runs and quantifying the uncertainty in the sequential information embedded in these patterns by calculating the average efforts required to align these multi-dimensional sequences for all possible pairs of predicted sequences. Because computational costs may become prohibitive in large-scale applications, several heuristic approaches are suggested and examined. Results indicate that (i) the suggested methods can represent uncertainty in predicted activity-travel sequences very well, (ii) that the suggested heuristics tend to approximate the calculated uncertainty based on all possible sequences, and (iii) that the heuristics however do not necessarily produce asymptotically more accurate results. Implications of these findings are discussed to complete the paper.
  Authors: Rasouli, Soora; Timmermans, Harry J.P.
  Authors: Rasouli, Soora; Timmermans, Harry J.P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-2511
• Methodology of Parking Analysis
  Abstract: Cities are faced with many challenges, in particular in relation to the mobility of people and the structure of land-use. Parking management, which makes the link between the fields of urban planning and transportation, is one of the crucial ways to meet these challenges. However, parking studies are a poorly covered area in transportation research. The main barrier to study parking is parking data availability.In the Greater Montreal Area, data from origin-destination (OD) surveys are helpful in understanding typical travel behavior. These surveys have been conducted for forty years and provide useful data to describe and model various spatial-temporal features of daily mobility.This research illustrates the use of OD survey data to develop indicators on parking spaces and use in a given area. This study confirms that the systematic processing of car driver trips from travel surveys allows developing vehicle accumulation profiles for various zones and, from these, derive theoretical parking capacities. This research provides an assessment of the quality of the estimation by comparing the estimations from OD survey to other sources of data, namely geographical data and field surveys.The paper shows that parking capacity is subject to high variability and highlights that its assessment is quite complex and must take into account regulation data that modulates the availability of the raw parking capacity according to different days and hours of the day.
  Authors: Diallo, Abdoulaye; Morency, Catherine; Saunier, Nicolas
  Authors: Diallo, Abdoulaye; Morency, Catherine; Saunier, Nicolas
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 299
  Paper Number: 13-2520
• Drivers’ Perception of Route Alternatives as Indicator for the Indifference Band
  Abstract: Although travel time is probably one of the most important attributes in route choice, the shortest time route is often not the preferred route according to several studies in the literature. This study tries to explain this finding by testing the hypotheses that choice makers may be able to estimate travel times correctly for routes they prefer, but that they are biased against alternatives even if these are faster. For a few choice sets of routes in the Dutch city of Enschede, respondents were asked to choose a route and provide their estimated travel times for both the preferred and alternative routes. These travel times were then compared with actual travel times from a license plate study. The comparison confirmed the hypotheses. For chosen routes, perceived travel times correspond quite well with actual travel times on average, while for non-chosen routes, perceived travel times are overestimated by 2 – 3 minutes on average. These results show that travelers are not able or do not want to evaluate routes objectively. This implies that within an indifference band of on average 2 – 3 minutes, they are probably not willing to alter their route choice, even if the traffic situation induced for example by traffic management measures, changes in a negative way for their preferred route.
  Authors: Vreeswijk, Jaap; Thomas, Tom; van Berkum, Eric; van Arem, Bart
  Authors: Vreeswijk, Jaap; Thomas, Tom; van Berkum, Eric; van Arem, Bart
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-2607
• Stated Adaptation Experiment for Individuals’ Time and Money Budget Allocation Decisions on Out-of-Home Leisure Activities
  Abstract: In this paper, we report the first findings of a web-based stated adaptation experiment for time and money budget allocation of individuals on their out-of-home leisure activities. This experiment is based on a model that is developed by the authors. It includes the data of 529 individuals which is a representative sample of the Dutch population. In the experiment, individuals are asked to adjust their time and money allocations including travel components in response to hypothetical scenarios such as a decrease in their income and increase in their working hours. Moreover, respondents are asked to report how they would make the changes in their budget allocation which gives a behavioral insight to the analysis. The data will allow the proposed models to be estimated. The paper focuses on the description of the new data collection instrument and application in a survey, and reports descriptive statistics of the stated-adaptation data obtained.
  Authors: Dane, Gamze
  Authors: Dane, Gamze
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-2608
• Generating Site-Specific Axle Load Factors for Florida's MEPDG Implementation
  Abstract: This study was undertaken to develop the axle load factors for the Mechanistic-Empirical Pavement Design Guide software. As originally designed, these data are presented to the pavement designers at one of three levels. The MEPDG Level 1 data are site-specific. The data are collected either at the site or at a nearby location on the same route that has similar traffic characteristics. This paper presents detailed information about the axle load data requirements of the Guide, the process followed for deriving Florida’s input values, and the resulting recommended values.
  Authors: Cunagin, Wiley; Reel, Richard Lowell; Ghanim, Mohammad; Roark, Drew; Leggett, Michael
  Authors: Cunagin, Wiley; Reel, Richard Lowell; Ghanim, Mohammad; Roark, Drew; Leggett, Michael
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2649
• Modeling Yard Crane Operators as Reinforcement Learning Agents
  Abstract: Due to the importance of drayage operations, operators at marine container terminals are increasingly looking to reduce the time a truck spends at the terminal to complete a transaction. This study introduces an agent-based approach to model yard cranes for the analysis of truck turn time. The objective of the model is to solve the yard crane scheduling problem (i.e. determining the sequence of drayage trucks to serve to minimize their waiting time). It is accomplished by modeling the yard crane operators as agents that employ reinforcement learning; specially, q-learning. The proposed agent-based, q-learning model is developed using Netlogo. Experimental results show that the q-learning model is very effective in assisting the yard crane operator to select the next best move. Thus, the proposed q-learning model could potentially be integrated into existing yard management systems to automate the truck selection process and thereby improve yard operations.
  Authors: Fotuhi, Fateme; Huynh, Nathan N.; Vidal, Jose M.; Xie, Yuanchang
  Authors: Fotuhi, Fateme; Huynh, Nathan N.; Vidal, Jose M.; Xie, Yuanchang
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-2671
• Exploring the Effects of Sensor Data Aggregation on Measuring Arterial Performance
  Abstract: Modern loop detector technology offers operations staff a wealth of data about their facilities. It should be possible to use these data to monitor, analyze, and communicate an arterial's performance, but dealing with gaps in the detector network, aggregated vehicle counts, and lags in receiving data can pose a challenge. This paper proposes six methods of using data from loop detectors to derive useful performance measures. A simulated arterial is employed to investigate each methods' accuracy under various conditions. Estimates are compared to simulated data visually, with input/output diagrams; and statistically, with simulated ground truth travel times. Methods for estimating travel time are applied to aggregated data and to varying detector densities. It is found that data from detectors combined with information about signal timing, saturation headways, and free flow travel times can be used by two of the methods described in the paper to provide accurate and useful estimates of average vehicle delay and average travel time, even in conditions where detectors are missing from intersections or detector data are aggregated.
  Authors: Wolfe, Michael; Monsere, Christopher M.; Bertini, Robert Lawrence
  Authors: Wolfe, Michael; Monsere, Christopher M.; Bertini, Robert Lawrence
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-2707
• Who are the ‘Drivers’ of Peak Car? A Decomposition of Recent Car Travel Trends for Six Industrialized Countries
  Abstract: This study investigates the contribution of the aging of the population and changes of travel behavior by different age groups to ‘peak car’ in France, Germany, Great Britain, Japan, Norway, and the USA. The term ‘peak car’ has been coined for the recent trend reversal in car travel development observed in some industrialized countries. Also in our study countries, car travel was characterized by growth for a long time but started to show signs of stagnation or even decrease in the last decade. We analyze underlying travel trends since the mid-1990s and use a trend decomposition based on descriptive statistics from National Travel Surveys and Laspeyres indices. The results indicate that relevant developments had different weight in shaping ‘peak car’ in our study countries. In many places, the aging of the population has been an important contributor to ‘peak car’. In Japan, aging was the most important factor limiting growth of car travel. In all study countries except the USA, where car ownership of seniors hasn’t grown further, increasing car ownership and car use of seniors has contributed to increasing car travel and thus has exerted a damping influence on ‘peak car’. Another important development were new travel trends among young adults. In three study countries the contribution of the decreased car orientation of young adults to ‘peak car’ is crucial: If young adults’ car ownership and / or car mode share would not have decreased, we would not have seen declining total car kilometers per capita in Germany and much stronger increases in Britain and Norway.
  Authors: Kuhnimhof, Tobias; Zumkeller, Dirk; Chlond, Bastian
  Authors: Kuhnimhof, Tobias; Zumkeller, Dirk; Chlond, Bastian
  Year: 2013
  Document Type: Paper
  Subject: International Activities; Data and Information Technology; Planning and Forecasting
  Session: 819
  Paper Number: 13-2715
• Systematic Approach for Hazardous Intersection Identification and Countermeasure Development
  Abstract: Safety performance functions (SPFs) are typically used to correlate geometric, traffic and environmental characteristics with total crashes and to identify hotspots which have high overall crash frequencies. However, with a distinct conflict pattern in vehicle maneuvers, each crash type is likely to associate with different risk factors. This study developed approach-level SPFs using a full Bayesian method to assess the safe effects of specific risk factors for rear-end, left-turn, right-angle, sideswipe and total crashes. To account for the spatial correlations among approaches at the same intersection, a random intersection-specific effect term was incorporated into each model. It was affirmed that these models were helpful in identifying high risk intersections with specific safety problems, and could serve as useful complements to general hotspot analyses using expected crash totals. In addition, it was found that certain variables (e.g. number of through lanes, median, and left-turn protection all on the entering approach) could have even contrary effects on crash occurrence of different types. Approach-level crash type models provide valuable insights in developing countermeasures aimed at reducing certain crash types and an improved ability in identifying deficiencies related to geometric and traffic characteristics for each intersection approach.
  Authors: Wang, Xuesong; Xie, Kun; Abdel-Aty, Mohamed A.; Tremont, Paul J.; Chen, Xiaohong
  Authors: Wang, Xuesong; Xie, Kun; Abdel-Aty, Mohamed A.; Tremont, Paul J.; Chen, Xiaohong
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 724
  Paper Number: 13-2698
• Stochastic Network Design Problem with Fuzzy Goals
  Abstract: The transportation network design problem (NDP) is a high capital investment decision-making problem that inherently involves both subjective and objective uncertainties as well as multiple objectives. Goal programming is a practically useful approach with an explicit consideration of planners’ goal setting and priority structure among the multiple objectives. In this paper, we develop a hybrid goal programming (HGP) approach for modeling both subjective and objective uncertainties simultaneously in the NDP decision-making process. Specifically, planners’ subjective uncertainty on the linguistic setting of goals and priority structure is characterized as fuzzy variables with nonlinear achievement and satisfaction functions, while the objective travel demand uncertainty is characterized as random variables with predefined probability distributions. The HGP NDP is formulated as a chance constrained model in a bi-level programming framework and solved by a random simulation and fuzzy evaluation based genetic algorithm solution procedure. Numerical examples are also provided to demonstrate the features of the proposed HGP approach in solving the NDP under uncertain environments.
  Authors: Xu, Xiangdong; Chen, Anthony; Cheng, Lin
  Authors: Xu, Xiangdong; Chen, Anthony; Cheng, Lin
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-2770
• Using Bicycles for Daily Commuting in Belo Horizonte, Brazil: Assessment of User Willingness Level with Spatial and Heterogeneity Considerations
  Abstract: The use of bicycles as a transportation mode for daily commuting trips has proven beneficial to both urban traffic conditions and travelers’ health. In order to efficiently design facilities and policies that will stimulate bicycle use, it is necessary to first understand people’s attitudes towards bicycle use, and the factors that may influence their preferences. Meanwhile, it should be expected that people’s willingness to use bicycles as their daily commuting mode is also subject to the influence of their neighbors and individual heterogeneity. This paper uses a spatial random parameter ordered probit model to analyze how travelers’ willingness to use bicycles is influenced by various socioeconomic factors in Belo Horizonte, Brazil, with the consideration of spatial dependency and heterogeneity across individuals. The model is estimated using the composite marginal likelihood (CML) approach, and results show that bicycle use is more favored by travelers with lower household income, lower commuting time, and who rent apartments. If a person is currently using a bicycle or walking to work, he/she would be most willing to commute with a bicycle in the future. Those currently commuting bymotorcycle and bus follow this group in terms of willingness to commute by bicycle in the future.. Car users seem to be difficult to convert to bicycle users. Moreover, the estimation shows clear evidence that significant personal heterogeneity indeed exists, especially for education level, necessitating the consideration of such an effect. The analysis framework developed in this study as well as the findings provide valuable insights into people’s opinion towards the use of bicycles for daily transportation.
  Authors: Wang, Xiaokun (Cara); Zhang, Dapeng; Magalhães, David
  Authors: Wang, Xiaokun (Cara); Zhang, Dapeng; Magalhães, David
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting
  Session: 735
  Paper Number: 13-2846
• Hybrid Approach for Clustering Vehicle Classification Data to Support Regional Implementation of Mechanistic-Empirical Pavement Design Guide
  Abstract: This paper develops a hybrid approach for analyzing vehicle classification data and applies the approach to a fused dataset from multiple jurisdictions in the Canadian Prairie Region. Application of the approach results in a set of regional default truck traffic classification groups (TTCGs) for use in the Mechanistic Empirical Pavement Design Guide (MEPDG). The hybrid approach is a conglomeration of three components: statistical clustering procedures, engineering judgment, and industry intelligence. By applying the hybrid approach, analysts receive the joint benefits of analytical rigor and industry-oriented pragmatism. Application of this approach results in eight TTCGs for the Canadian Prairie Region, which exhibit distinct differences from the default distributions developed for national use in the United States.The benefits of the hybrid approach on fused datasets include: (a) the statistical strength gained from utilizing additional classification data, (b) the development of TTCGs that better reflect the diversity of patterns in the Region, and (c) the potential for improved ability to capture future shifts in truck traffic characteristics based on experience gained in other jurisdictions. The study also identifies limitations to the hybrid approach that should be considered. These limitations include varying data quality between jurisdictions, the sensitivity of low-volume sites to changes in industry patterns and the ability to track these changes, and a shortage of continuous classification sites in the Region. With a clear understanding of its benefits and limitations, the hybrid approach can be applied to truck traffic data analyses in any jurisdiction.
  Authors: Reimer, Mark Jonathon; Regehr, Jonathan D.
  Authors: Reimer, Mark Jonathon; Regehr, Jonathan D.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management
  Session: 796
  Paper Number: 13-2849
• Impact of Different Trucks on Pavement Design and Analysis: MEPDG Sensitivity Study Based on Data from Long-Term Pavement Performance Specific Pavement Studies Traffic Pooled Fund Study
  Abstract: This investigation was conducted to assess sensitivity of Mechanistic-Empirical Pavement Design Guide (MEPDG) outcomes to normalized axle load spectra (NALS) representing different loading conditions observed in Long Term Pavement Performance (LTPP) Specific Pavement Studies Traffic Pooled Fund Study (SPS TPF). The goal was to determine what vehicle classes and axle types are likely to cause differences in pavement design outcomes using the MEPDG, considering range of axle loading conditions. Significant differences in the outcomes would support the need for axle loading characterization beyond simple default value, while the absence of differences would indicate that load spectra from different sites could be combined to develop a default for a given vehicle class and axle type. The analysis also investigated when use of different default load spectra for class 9 vehicles would provide only marginal benefit due to low sensitivity of MEPDG outcomes. These results were used to develop recommendations for creation of axle loading defaults for MEPDG.
  Authors: Selezneva, Olga I.; Ramachandran, Aditya N.; Mustafa, Endri; Carvalho, Regis L.
  Authors: Selezneva, Olga I.; Ramachandran, Aditya N.; Mustafa, Endri; Carvalho, Regis L.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2890
• Practical Guidelines for Development of MEPDG Axle Loading Defaults Based on Findings from Long-Term Pavement Performance Specific Pavement Studies Traffic Pooled Fund Study
  Abstract: This paper presents methodology for development of MEPDG axle loading defaults and practical guidelines based on the findings from LTPP SPS TPF study. It introduces a concept of Tier 1 and Tier 2 axle loading defaults and provides recommendations when these defaults should be used, along with step-by-step instructions how to create these defaults. Because many truck characteristics differ from state to state, it would be beneficial for state highway agency to develop their own axle loading defaults. Methodology presented in this paper can be utilized by state highway agencies to develop their MEPDG axle loading defaults.
  Authors: Selezneva, Olga I.; Hallenbeck, Mark E.
  Authors: Selezneva, Olga I.; Hallenbeck, Mark E.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-2908
• Automatic Classification of Road Users' Travel Modes in a Mixed-Traffic Roundabout
  Abstract: The objective of this paper is to present and evaluate an automated road-users classification procedure. The classification is based on the analysis of the motion pattern attributes associated with the trajectories of each road-user type; vehicles, pedestrians and cyclists. A novel approach for features selection is proposed where singular spectrum analysis identifies the main harmonics (speed variation) characterizing the movements trajectories. A constraint-based decision procedure is then applied on the selected features to categorize the road-users. Performance evaluation of the proposed classification is presented. Validation of the procedure is undertaken using real world data set collected at a newly designed mixed traffic roundabout in Greater Vancouver, British Columbia. Satisfactory results were demonstrated and evaluated through performance measures with a reported classification accuracy of around 80 percent. The goal of this research is to improve the understanding of road-users behavior in order to enhance the riding condition and provide an efficient and safe commuting environment. The main benefit of this research is to apply classification as a first step in the activity and behaviour recognition of road-users in traffic scenes.
  Authors: Zaki, Mohamed H.; Sayed, Tarek
  Authors: Zaki, Mohamed H.; Sayed, Tarek
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-2894
• The Language of Driving: Advantages and Applications of Symbolic Data Reduction for Naturalistic Driving Data Analysis
  Abstract: Recent advances in onboard vehicle data recording devices have created an abundance of naturalistic driving data. The amount of data exceeds the resources available to analyze it, forcing researchers to focus on analyses of "critical events," which are identified using simple heuristics. This critical event analysis eliminates the context that can be critical in understanding driver behavior, reducing the generalizability of the analysis. This work introduces a method of naturalistic driving data analysis that will allow researchers to examine entire datasets by reducing them by over 90%. The method utilizes a symbolic data reduction algorithm, Symbolic Aggregate approXimation (SAX), which reduces time-series data to a string of letters. SAX can be applied to any continuous measurement and SAX output can be reintegrated into a dataset to preserve categorical information. This work explores the application of SAX to speed and acceleration data from a naturalistic driving dataset and demonstrates SAX's integration with other methods that can begin to tame the complexity of naturalistic data.
  Authors: McDonald, Anthony D.; Lee, John D.; Aksan, Nazan S.; Dawson, Jeffrey; Tippin, Jon; Rizzo, Matthew
  Authors: McDonald, Anthony D.; Lee, John D.; Aksan, Nazan S.; Dawson, Jeffrey; Tippin, Jon; Rizzo, Matthew
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-2947
• Comparison of Sichel and Negative Binomial Models in Estimating Empirical Bayes Estimates
  Abstract: Traditionally, transportation safety analysts have used the empirical Bayes (EB) method to improve the estimate of the long-term mean of individual sites and to identify hotspots locations. The EB method combines two different sources of information: (1) the expected number of crashes estimated via crash prediction models, and (2) the observed number of crashes at individual sites. Crash prediction models have extensively been estimated using a negative binomial (NB) modeling framework due to the over-dispersion commonly found in crash data. Recent studies have shown that the Sichel (SI) distribution provides a promising avenue for developing crash prediction models. The objective of this study is to examine the application of the SI model in calculating EB estimates. To accomplish the objective of the study, the SI models with a fixed/varying dispersion term are developed using the crash data collected at 4-lane undivided rural highways in Texas. The important conclusions can be summarized as follows: (1) the selection of the crash prediction model (i.e., the SI or NB model) will affect the value of weight factor used for estimating the EB output; (2) the identification of hazardous sites, using the EB method, can be different when the SI model is used. Finally, a simulation study designed to examine which crash prediction model can better identify the hotspot is recommended as our future research.
  Authors: Zou, Yajie; Lord, Dominique; Zhang, Yunlong; Peng, Yichuan
  Authors: Zou, Yajie; Lord, Dominique; Zhang, Yunlong; Peng, Yichuan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-2938
• Extracting 3d Transportation Features From Kinect Sensor Array Data
  Abstract: Three-dimensional modeling of transportation infrastructure assets such as roadways, bridges, signage, guard rails, etc., provide engineers an analysis framework that previously was too labor intensive and cost prohibitive to manually collect. The emerging industry standard for point cloud data collection is the use of either airborne or terrestrial based Light Detection and Ranging (LiDAR). The problem is that LiDAR hardware currently costs tens to hundreds of thousands of dollars and requires trained personnel to operate. Described within this paper are examples of how a low cost consumer grade electronic, the Microsoft Kinect sensor, can be used to collect point cloud data similar to terrestrial based LiDAR. For less than two hundred and fifty dollars, a Kinect sensor can be used by engineers to capture a wide range of transportation features such as bridge underpass heights, guard rail features, road signs, and the distance of the nearest roadside object. The approach presented herein automatically locates bridge under-passes with the Kinect Sensor, calculates the lowest clearance, and exports that data in an attributed GIS shapefile. In addition, guard rails and road signs can be identified and measured from Kinect sensor data.
  Authors: Hudnall, Matthew; Graettinger, Andrew J.
  Authors: Hudnall, Matthew; Graettinger, Andrew J.
  Year: 2013
  Document Type: Paper
  Subject: Construction; Data and Information Technology; Design
  Session: 729
  Paper Number: 13-2733
• Hidden Markov Models for Vehicle Tracking with Bluetooth
  Abstract: Bluetooth is a short range communication protocol. Bluetooth-enabled devices can be detected using road-side equipment, and each detected device reports a unique identifier. These unique identifiers can be used to track vehicles through road networks over time. The focus of this paper is on reconstructing the paths of vehicles through a road network using Bluetooth detection data. A method is proposed that uses Hidden Markov Models, which are a well-known tool for statistical pattern recognition. The proposed method is evaluated on a mixture of real and synthetic Bluetooth data with GPS ground truth, and it outperforms a simple deterministic strategy by a large margin (30%-50%) in this case.
  Authors: Lees-Miller, John D.; Wilson, R. Eddie; Box, Simon
  Authors: Lees-Miller, John D.; Wilson, R. Eddie; Box, Simon
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-3032
• Full Bayes Methods for Road Safety Studies: Does Prior Specification Matter?
  Abstract: This paper investigates the effect of prior assumptions when applying Full Bayes (FB) methods in road safety analysis. The effect of prior choice is evaluated in the accuracy of model parameters, hotspot identification, goodness-of-fit, and treatment effectiveness index in before-after studies. Particular attention is devoted to conditions with lack of data referenced as the low-mean and small-sample problem. In this research, informative, semi-informative, and no-informative priors were determined based on past published studies. Using a simulation framework, various scenarios of sample size and crash occurrence mean are evaluated. Simulated data is generated based on two real databases of divided/undivided rural highway segments in New York and Texas. Diverse sample mean values were obtained considering different time periods (number of years) and classifying accidents in injury-fatal and total accidents. Among other results, it was found that under low-mean and small sample conditions, the outcomes can be significantly biased. However, the introduction of informative priors can still make feasible observational before-after studies when working with small number of observations from treatment and/or comparison sites. Informative priors can help provide more accurate estimates of the treatment effectiveness. Finally, in accordance with previous works, it was shown that the inverse dispersion parameter is significantly affected by prior specifications; nevertheless, regression parameters, goodness-of-fit, and hotspot identification are only slightly sensitive to prior choices.
  Authors: Miranda-Moreno, Luis Fernando; Heydari, Mohammad; Amador-Jimenez, Luis
  Authors: Miranda-Moreno, Luis Fernando; Heydari, Mohammad; Amador-Jimenez, Luis
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-3042
• Activity Pattern Recognition by Using Support Vector Machines with Multiple Classes
  Abstract: The focus of this paper is to learn the daily activity engagement patterns of travelers by using a nontraditional model called Support Vector Machines (SVM) that is widely used in Artificial intelligence and Machine Learning. It is postulated that an individual’s choice of activities depends not only on socio-demographic characteristics but also on previous activities of individual at the same day. In the paper, Markov Chain models are used to study the sequential choice of activities. The dependency between activity type, activity sequence and socio-demographic data are captured by employing Conditional Random Fields. In order to learn model parameters, we use sequential multinomial logit model and multiclass Support Vector Machines (K-SVM) with two different dependency structures. In the first dependency structure, it is assumed that type of activity at time t depends on the last previous activity and sociodemographic data, whereas in the second structure we assume activity selection at time t depends on all previous activity types of the individual on the same day and her sociodemographic characteristics. The models are applied to data drawn from Orange County and San Diego County households and a comparison of the accuracy of estimation indicates the superiority of K-SVM with first dependency structure over the other models tested. Additionally, we show that by using different sets of explanatory variables or tuning parameters of the kernel function in K-SVM, its accuracy in estimating activity patterns increases.
  Authors: Allahviranloo, Mahdieh; Recker, Will
  Authors: Allahviranloo, Mahdieh; Recker, Will
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-3046
• Developing a Truck Corridor Crash Severity Index
  Abstract: According to the United States Department of Transportation (USDOT) estimates, over 500,000 truck accidents occur every year. Of that number, approximately 5,000 trucking accidents result in fatalities. Compared to extensive studies conducted on freeway truck safety, the research on arterial streets is considerably disproportionate. Making the connections between truck traffic generators, arterial streets are key links in door-to-door deliveries. There is an urgent need to study truck safety on arterial streets because of the strong growth of truck traffic. Truck related crashes are expected to be reduced through the careful planning of the location, design, and operation of driveways, median openings, street connections and street sections. By collecting extensive data on selected arterial corridors that are heavily used by trucks, truck crash frequency and severity contributing factors have been identified using negative binomial model and multinomial logit (MNL) model, respectively. Subsequently, a crash severity index (CSI) for the truck arterial corridors was developed. The findings from the study will not only benefit state and local agencies in planning, design, and manage a safer truck arterial corridor, but also help carriers to optimize their routes from the safety perspective.
  Authors: Qin, Xiao; Sultana, Most Afia; Chitturi, Madhav V.; Noyce, David A.
  Authors: Qin, Xiao; Sultana, Most Afia; Chitturi, Madhav V.; Noyce, David A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 433
  Paper Number: 13-3047
• Accelerated Damage to Low-Volume Highways due to Natural Gas Well-Drilling Activity in Arkansas
  Abstract: Natural gas drilling activity began in 2006 within the Fayetteville Shale Play Area (FSPA), a 7,400 square mile (19,166 square kilometer) area in north central Arkansas. The FSPA is located mainly within 10 Arkansas counties and contains approximately 2,580 miles (4,152 kilometers) of highways, with 1,338 miles (2,153 kilometers) of those considered lower volume highways (LVH). More than 230 miles (370 kilometers) of highways in the FSPA were also weight-restricted routes due to their lack of structural strength. By 2007, over 1,100 gas wells were being developed. By 2010, the number of active wells had grown to 3,575.This drilling activity led to the rapid deterioration of many of the lower volume state highways that were never designed to endure these types of loadings. The Arkansas State Highway and Transportation Department (AHTD) began to collect data and document the increase in truck traffic and the resulting pavement damage in late 2007 as the cost to maintain these routes skyrocketed and considerable public complaints were voiced.AHTD monitored and collected pavement performance information in 2008, 2009 and 2010 on 28 lower volume highway sections. Since these sections endured truck traffic loadings easily exceeding the expected 20-year accumulated traffic loadings in just a few months, the AHTD was able to document the progression of pavement damage over these routes and report these findings to the Arkansas Highway Commission.
  Authors: Wright-Kehner, Elisha; Meadors, Alan
  Authors: Wright-Kehner, Elisha; Meadors, Alan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Energy; Pavements
  Session: 534
  Paper Number: 13-3099
• Functionings Enhanced by Social Networks in Elder’s Activity Participations: The Capability Approach
  Abstract: Social networks can generate desires to perform activities with others (activity opportunities), while it can also provide mobility especially for those who cannot use a car (mobility support). In this sense, at least two different functionings could be enhanced by social networks, but these two aspects have not been well distinguished in activity-travel behavior analysis. This study first attempts to develop a conceptual framework based on Senfs Capability Approach to shed light on the multiple roles of social networks in elderfs activity-travel decisions. We then develop a simple operational method by utilizing logsum measures in order to empirically identify the roles of social networks and these impacts on activity-travel behavior. The empirical analysis is conducted focusing on elderfs social, shopping and leisure activity participations in a typical newtown in Hiroshima, Japan. The results show that family members may only contribute to the increase in mobility support, while friends may contribute to both social network roles in the case study area. We also find that activity opportunities have positive impacts on social and shopping activity participations, but less significant impacts on leisure activities.
  Authors: Chikaraishi, Makoto; Fujiwara, Akimasa; Kuwano, Masashi; Zhang, Junyi
  Authors: Chikaraishi, Makoto; Fujiwara, Akimasa; Kuwano, Masashi; Zhang, Junyi
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-3112
• Weather’s Impact on Travel Time and Travel Time Variability in New York City
  Abstract: In this study, the impact of weather conditions on travel time and travel time variability in New York City is investigated using Classification and Regression Trees (C&RT). For this purpose, taxi GPS data provided by the New York City Taxi and Limousine Commission (TLC) with more than 370 million records is merged with historical weather data. For all day-of-week (DOW), time-of-day (TOD) and weather condition categories, the impact of weather on the mean and mode of travel time distributions and on the coefficient of variation as a measure for variability are analyzed. It is found that the level of travel time variability changes across DOW-TOD-weather categories and that weather has a higher impact on travel time and variability during less congested periods. The literature has shown that inclement weather slows traffic: a major finding of this study is that it also reduces traffic variability, a finding that would seem counter-intuitive. Using a rich dataset and the appropriate analytical methods, the present study contributes valuable insights to the understanding of travel time variability in an urban context.
  Authors: Yazici, M. Anil; Kamga, Camille; Singhal, Abhishek
  Authors: Yazici, M. Anil; Kamga, Camille; Singhal, Abhishek
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-3137
• Identifying Precrash Factors Between Cars and Trucks on Interstate Highways: Mixed Logit Model Approach
  Abstract: This research investigates the factors that lead to three manners of collision that occur in the same direction of roadway in multilane interstate highways: rear-end, angle and sideswipe. A Mixed Logit (MXL) model was developed to estimate the probability of rear-end, angle and sideswipe collisions as functions of vehicle-following attributes and other pre-crash driving maneuvers immediately before collisions. This research emphasizes collisions among passenger cars and large trucks since their vehicular characteristics play a major role in driving behavior. Results show that driving behavior is different when vehicular characteristics are different and when roles of the vehicle driven and stricken are grouped according to cars and trucks. This research contributes to a better understanding of the differences in unsafe driving acts between cars and trucks, and implications on future policies on car and truck drivers.
  Authors: Romo, Alicia; Hernandez, Salvador; Cheu, Ruey Long
  Authors: Romo, Alicia; Hernandez, Salvador; Cheu, Ruey Long
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3149
• Understanding Urban Human Activity and Mobility Patterns Using Large-Scale Location-Based Data from Online Social Media
  Abstract: Location-based check-in services enable individuals to share their activity-related choicesproviding a new source of human activity data for researchers. In this paper urban humanmobility and activity patterns are analyzed using location-based data collected from socialmedia applications (e.g. Foursquare and Twitter). We first characterize aggregate activitypatterns by finding the distributions of different activity categories over a city geographyand thus determine the purpose-specific activity centers. We then characterize individualactivity patterns by finding the timing distribution of visiting different places depending onactivity category. We also explore the frequency of visiting a place with respect to the rankof the place in individual's visitation records and show interesting match with other resultsbased on mobile phone mobility data. We finally propose a physics-based model of humanmobility patterns that can explain the scaling laws observed in the data.
  Authors: Hasan, Samiul; Ukkusuri, Satish V.; Zhan, Xianyuan
  Authors: Hasan, Samiul; Ukkusuri, Satish V.; Zhan, Xianyuan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 299
  Paper Number: 13-3172
• Handling Uncertainty in Transit Project Evaluation and Rating Process: A Comparison between the Existing FTA Approach and a Fuzzy Inference Approach
  Abstract: A fuzzy inference approach that ranks proposals for major transit projects is proposed, and its performance is compared with the existing approach used by the US Federal Transit Administration’s (FTA) New Starts Program. The FTA’s approach uses a rigid mathematical process in which 24 attributes of a proposal are scored initially. These scores are aggregated multiple times to obtain a single overall rating for the proposal, on which the proposal’s funding recommendation is made. In this approach, a small difference in the initial score can make significant differences in the final score; the final score is not stable with respect to small perturbations in the initial scores of the attributes. In any evaluation, there is always room for subjective judgment and associated uncertainty to enter, when determining the score of an attribute, when determining the breakpoints on the scoring scale, and when determining the value of the weight of the attributes. The proposed fuzzy inference approach incorporates fuzziness and approximation that is associated with the evaluation process and preserves it through the calculation process. The two approaches, the FTA’s and the proposed one, are compared using the data in the 2012 and 2013 reports of FTA’s New Starts Program proposal evaluation. The proposed fuzzy inference approach is found to be robust in dealing with evaluator’s uncertainty in the initial scores. The final score is found to be more stable than the FTA method, with respect to small changes in the initial values, weights, and breakpoint on the performance scale.
  Authors: Kikuchi, Shinya; Kronprasert, Nopadon
  Authors: Kikuchi, Shinya; Kronprasert, Nopadon
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 530
  Paper Number: 13-3173
• Optimal Number and Location of Node-Based Sensors for Travel Time Data Collection in Networks
  Abstract: Travel time prediction is highly used in traffic management and planning and its accuracy relies on the accuracy of travel time data. Various methods are being used in collecting travel time data using different types of sensors such as link-based and node-based sensors. Recently, a new method in collecting travel time data is introduced that is called Bluetooth technology which detects Bluetooth devices in the vehicles to determine their travel time. Bluetooth sensors are generally node-based sensors.Despite the amount of literature available in sensor location problem, a few discuss node-based sensors with the application of collecting travel time. Different projects in collecting travel time data using Bluetooth Sensors motivated the study of sensor location problem for installing Bluetooth sensors and in a general sense, node-based sensors. The goal of this study is to find the optimal number of node-based sensors and their deployment location in a network in order to collect travel time data with a high reliability. Two formulations are proposed for modeling this problem. The formulations consider a new set of reliability factors. Using these formulations, sensor location problem can be solved optimally for large networks. The proposed formulations are not restricted to Bluetooth sensors and can also be applied to any node-based sensor location problem. Various case studies using real world networks are conducted to compare the results obtained from both proposed formulations with available mothodologies in the literature. Findings of the case studies are reported in the paper.
  Authors: Asudegi, Mona; Haghani, Ali
  Authors: Asudegi, Mona; Haghani, Ali
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-3128
• Examining Differences Between Travelers’ Revealed Versus Actual Travel Time Savings
  Abstract: Revealed preference surveys are one of the most common ways to obtain information on how travelers use a given transportation facility. In a revealed preference survey the respondents are asked questions related to their recent travel. In a survey conducted in 2010 on Houston Katy Freeway travelers, respondents were asked about their travel experience using the new Katy Freeway Managed Lanes (MLs). They were asked if they experienced any travel time savings by using the MLs. This study examined any difference between their perceived and actual travel time savings. This study found that travelers overestimate the travel time savings they experience by traveling on the MLs. The magnitude of misperception varied with individuals with an average value of 11 minutes. Linear regression models were fit to model the misperception of the travel time and found that both trip characteristics and respondent socio-economic characteristics had an effect on the magnitude of misperception of travel time savings. Respondents’ trip purpose, age, gender, and income were found to be significant predictors of how well they estimated their travel time savings.
  Authors: Devarasetty, Prem Chand; Burris, Mark W.; Huang, Chao
  Authors: Devarasetty, Prem Chand; Burris, Mark W.; Huang, Chao
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-3202
• Reexamination of Traffic Data Preparation for the Mechanistic-Empirical Pavement Design Guide
  Abstract: An initial study to characterize traffic data for the Mechanistic Empirical Pavement Design Guide (MEPDG), performed in 2004, was reexamined. The objectives were (1) to update the traffic data library with the latest available data, (2) to compare the difference between the initial and new datasets, (3) to investigate the possible influence on pavement design due to different traffic datasets, and (4) to establish a workflow for traffic data operations at the Arkansas State Highway and Transportation Department (AHTD). Traffic data collected from weigh-in-motion stations between 2002 and 2010 were analyzed. The new dataset provided better quality than old dataset; overall, 91% of classification data and 13% of weight data passed the quality check. While statewide traffic patterns did not change significantly over the past 10 years, different Truck Traffic Classification (TTC) groups were observed – primarily due to the sensitivity of TTC to the amount of Class 13 trucks. New statewide and TTC-based volume adjustment factors and axle load spectra were developed. The influence of the adjusted traffic inputs on pavement design was studied by modeling two existing projects in DARWin-ME. The adjusted traffic data resulted in 8 years difference for the predicted design life. It is recommended that state-specific data should be applied in pavement design whenever possible. In addition, the traffic data library for the MEPDG should be periodically reviewed and updated as necessary.
  Authors: Hall, Kevin D.; Xiao, Danny X.; Nguyen, Vu T. D.; Wang, Kelvin C. P.
  Authors: Hall, Kevin D.; Xiao, Danny X.; Nguyen, Vu T. D.; Wang, Kelvin C. P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-3213
• Comparison of MEPDG Nationally Calibrated Traffic Inputs with Weigh-in-Motion Measurements in Alberta, Canada
  Abstract: Mechanistic-Empirical Pavement Design Guide (MEPDG) uses load spectra and number of axle applications to characterize traffic loads for the pavement designs, as a substitute for the equivalent single axle load (ESAL) approach. Alberta Transportation (AT) installed six weigh-in-motion (WIM) systems to collect the traffic inputs for a reliable pavement design using the MEPDG. The traffic data from the six WIM in Alberta was compared to the default values in the MEPDG Software for two consecutive years of 2009 and 2010. Reasonable agreements were observed for hourly and monthly adjustment factors; while truck traffic classifications and axle load distributions deviated from the MEPDG’s default values at some WIM stations. The influence of these differences on the performance of a typical Asphalt Concrete (AC) pavement for Alberta conditions was established through a sensitivity analysis. It was found that alligator cracking is the most sensitive to truck traffic classifications (specifically the distribution of truck Class 13). Using the truck distribution for Highway 16:06 based on the WIM measurements required an increase in the pavement thickness design. AC rutting was also found to be sensitive to all the studied variables including truck distribution, single and tandem axle load spectra; while IRI was not affected significantly by the changes in the variables under study.
  Authors: Nassiri, Somayeh; Farkhideh, Naser; Bayat, Alireza
  Authors: Nassiri, Somayeh; Farkhideh, Naser; Bayat, Alireza
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-3220
• Uncovering Influence of Commuters' Perception on Reliability Ratio
  Abstract: The dominant method for measuring values of travel time savings (VOT), and values of travel time reliability (VOR) is discrete choice modeling. Generally, the data sources for these models are: stated choice experiments, and revealed preference observations. There are few studies using revealed preference data. These studies have only used travel times measured by devices such as loop detectors, and thus the perception error of travelers has been largely ignored. In this study, the influence of commuters' perception error is investigated on data collected of commuters recruited from previous research \citep{Carrion2012B, Zhu2010}. The subjects' self-reported travel times from surveys, and the subjects' travel times measured by GPS devices were collected. The results indicate that the subjects reliability ratio is greater than 1 in the models with self-reported travel times. In contrast, subjects reliability ratio is smaller than 1 in the models with travel times as measured by GPS devices.
  Authors: Carrion, Carlos; Levinson, David M.
  Authors: Carrion, Carlos; Levinson, David M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-3248
• On the Way or Around the Corner? Observed Refueling Choices of Alternative-Fuel-Vehicle Drivers in Southern California
  Abstract: Limited refueling infrastructure is an oft-cited barrier to alternative fuel vehicle (AFV) adoption, but empirical data on AFV driver refueling behavior are rare. To address this need, we surveyed 259 drivers of compressed natural gas (CNG) vehicles in Southern California at five stations across the metropolitan area. The key survey questions concerned the stops immediately before and after refueling and the driver’s home location. Using GIS, we analyze the least travel-time routes and the station chosen to provide insight into what drivers consider to be their most convenient refueling location. Specifically, we focus on whether they select stations nearer to home or on routes that require the least deviation, when faced with a choice between the two—that is, when no station satisfies both criteria. We demonstrate that, in such situations, CNG drivers are ten times more likely to select a station more on their way between a given origin and destination than a station closest to home. This finding supports the notion that flow-based optimal location models may be more appropriate than point-based models for planning early AFV refueling infrastructures, and that locations near high-volume roads may be ideal early candidates for station sites.
  Authors: Kelley, Scott; Kuby, Michael
  Authors: Kelley, Scott; Kuby, Michael
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-3280
• Characteristics and Contributing Factors of On-Duty Struck-by Crashes
  Abstract: Emergency responders and roadway workers are on-duty to assist incidents and perform roadway maintenance and construction, which benefits all road users. However, the location of their work implies that they are exposed to being struck by surrounding traffic. On-duty struck-by crashes are defined as a traffic incident that involves police officers, roadway workers, firefighters and EMT/First Responders, who are hit by a motorist while on duty assisting an incident or at a work zone. The objective of this research is to summarize and analyze struck-by crashes. Initial crash data are extracted from the WisTransPortal on Wisconsin’s State Trunk Network (STN). Data are selected from 2000-2010 and included several filtering steps and manual identification for data reduction. Two hundred sixty-five crashes are identified as struck-by crashes and the characteristics and contributing factors are analyzed. Responder and worker struck-by crashes are separately analyzed with different characteristics shown, all STN crashes from 2000-2010 are used as a comparison group. Characteristics are classified into crash, highway, environment, and on-duty person characteristics. Driver contributing factors are also presented. Results show that for responders crashes, police officers are the predominant type of on-duty person. A large proportion of responder crashes occurred on rural interstate highways. Speeding or “too fast for conditions” is the key driver factor that leads to struck-by crashes at incidents and adverse roadway/weather conditions are the most significant environmental factor. Most emergency responder struck-by crashes occur when responders are assisting traffic incidents. On the other hand, for roadway workers, flagmen hit by surrounding traffic account for around half of all worker struck-by crashes, worker crashes are likely uncorrelated with adverse weather, roadway or lighting conditions. Inattentive driving of civilian drivers is the most significant contributing factor. These results could provide a basis for countermeasures to protect emergency responders and roadway workers.
  Authors: Yu, Lang; Bill, Andrea R.; Chitturi, Madhav V.; Noyce, David A.
  Authors: Yu, Lang; Bill, Andrea R.; Chitturi, Madhav V.; Noyce, David A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3317
• Toward a Flexible System for Pedestrian Data Collection Using Microsoft Kinect Motion-Sensing Device
  Abstract: Information about pedestrian activity, including volumes, walking speed, and trajectories, are used by transportation agencies and researchers for planning, design and analysis purposes. There exist a number of technologies for automatic pedestrian data collection; however all have inherent limitations either in functionality or in monetary cost. Also, most technologies only provide counts. This paper proposes the use of an inexpensive motion sensing device: the Microsoft Kinect, which is able to track multiple people in low-light conditions and could be combined with existing video based daytime tracking. The tracking software and speed estimation methodologies are described, and indoor and outdoor studies show the system’s effectiveness at determining pedestrian volumes and walking speeds. The accuracy of speed data is very satisfactory, with correlation of 98% or more with respect to video data validation speeds. The accuracy of pedestrian volume data varies with traffic conditions, however in low to moderate traffic conditions its performance is accept able with an under counting error of about 8%. The different applications of the sensor and its complementarity with other sensors is discussed, this being the first step towards a multi-sensor system.
  Authors: Charreyron, Samuel; Jackson, Stewart; Miranda-Moreno, Luis Fernando
  Authors: Charreyron, Samuel; Jackson, Stewart; Miranda-Moreno, Luis Fernando
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists
  Session: 640
  Paper Number: 13-3284
• Evolutionary Game Theoretic Approach to Rear-Ending Events on a Congested Freeway
  Abstract: Rear-ending crashes on freeways contribute significantly to non-recurring congestion. Reducing these events would then significantly improve freeway capacity, particularly during peak hours. Although promising countermeasures, such as variable speeds limits, changeable message signs, and vehicle-based improvements, are under consideration, at present there is a shortage of demonstrably proven countermeasures targeted to freeway rear-ending crashes. Liability rules, where the direct cost associated with a crash is divided between the drivers and/or their insurance companies, are a primary mechanism for influencing the occurrence of freeway rear-ending crashes, and can be expected to continue in importance in the future. This paper describes an exploratory effort at using concepts from evolutionary game theory to predict the effects of liability rules on rear-ending crashes. In a typical two-vehicle car following scenario, driving behavior can be associated with a utility which each driver expects to achieve depending upon his/her and the opponent’s action. Such interactions between leader and follower are modeled as the outcome of an evolutionary process, where drivers with different driving behaviors are randomly and repeatedly matched against each other to play a two-player game. The outcome of these games determines the fraction of drivers pursuing a particular driving strategy for the next phase of the game. The stable long-run distribution of driving strategies is then used to predict the proportion of drivers who are more likely to be involved in a rear-ending accident. It turns out that when direct crash costs are allocated evenly to the involved drivers, a population where all drivers act to avoid crashes is not evolutionarily stable.
  Authors: Chatterjee, Indrajit; Davis, Gary A.
  Authors: Chatterjee, Indrajit; Davis, Gary A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3326
• Statistical and Analytical Modeling of Children’s Travel Behavior:Some Evidence on the Cultural Effects
  Abstract: Children lifestyle including their travel and activity pattern is highly influenced by their household characteristics. Household socioeconomic characteristics determine most aspects of children's life including their school location, and school travel mode choice. A statistical analysis and discrete choice modeling approach is conducted in this paper to investigate the primary school children travel behavior. This study focused on representative trip chain, mode choice, school location and escort status as fundamental elements in children’s trips pattern. Contingency analysis is used to check for the correlation among explanatory variables such as household socioeconomics, gender and city with intended travel behavioral aspects. Statistical analysis revealed that gender and family car ownership are two of the most efficacious parameters. A two stage discrete choice model is used for modeling decision process among children and their parents in their behavior. This study shows that parent’s attitude about their children is highly affected by child’s gender and this is due to some cultural and religious believers of Iranian household.
  Authors: Arman, Mohammad Ali; Kalantari, Navid
  Authors: Arman, Mohammad Ali; Kalantari, Navid
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-3669
• Imputing Trip Purpose Based on GPS Travel Survey Data and Machine Learning Methods
  Abstract: In the recent decades, increasing number of travel researchers show interest in travel behavior research based on GPS/GIS technology. The challenge of successfully utilizing GPS-based data is the efficient post-processing method that could generate the essential components as accurately as possible in travel behavior researches such as travel time, trip purpose, travel mode, and trip length. This paper concentrates on part of the GPS data post-processing: trip purpose derivation, and explores the feasibility of automating trip purpose detection employing machine learning method with geospatial location data, the land use data, and the in-practice GPS-based survey conducted by University of Minnesota. Furthermore, it evaluates the impacts of different land use coding methods based on polygon-level, geo-coded home/work locations and Point of Interest (POI) land use data combined with different machine learning methods including decision tree, support vector machine and metalearner. A heterogeneous sample of 2238 trip records with decoded 7 trip purposes is employed. Results show that under all the machine learning methods, the cluster-based land use coding method is exceeded by the closest POI land use coding method, while amongst the three machine learning methods, the metalearner has the best performance to classify the trip purpose. Based on the metalearner and the data set using the closest POI land use coding method, the highest classification accuracy 80.5817% can be achieved.
  Authors: Lu, Yijing; Zhu, Shanjiang; Zhang, Lei
  Authors: Lu, Yijing; Zhu, Shanjiang; Zhang, Lei
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-3177
• Estimating Rear-End Accident Probabilities at Signalized Intersections: Comparison Study of Intersections With and Without Green Signal Countdown Devices
  Abstract: Rear-end accidents are the most common accident type at signalized intersections, since the diversity of actions taken increases due to signal change. Green signal countdown devices (GSCD), which have been widely installed in Asian countries are thought to have the potential of improving capacity and reducing accidents, but some negative effects on intersection safety have been observed in practice, for example, an increase of rear-end accidents. Based on the field observation and data collection at four adjacent intersections along an arterial in Suzhou, China, in which two are GSCD intersections, a total of 3350 samples of timestamps associated with 557 vehicles have been collected. A microscopic modeling approach has been applied to estimate the rear-end accident probability during phase transition interval. The rear-end accident probability is determined by the probabilities: (1) a leading vehicle makes a ¡°stop¡± decision, which is formulated by using a binary logistic model and (2) the following vehicle fails to stop in the available stopping distance, which is closely related to the critical deceleration used by the leading vehicle. Based on Monte-Carlo simulation results, rear-end probabilities at GSCD intersections and NGSCD intersections have been compared, it shows that the installation of GSCD devices creates a double-edge sword to vehicle safety and the negative effects are thought to be greater. Though GSCD devices can reduce rear-end accident probability for vehicles that have no difficulties to make stop/go decisions when approaching the stop line during phase transition interval, they increase rear-end accident probability for vehicles that stop/go decision is not easy to make. Further, correlation between speeds and rear-end accidents has been investigated, the results reveal that too low speeds are more likely to provoke rear-end accidents at certain sections of the approach lane during phase transition interval.Based on the above research findings, we recommend that GSCD devices should be cautiously installed and too low speed at approach lanes during phase transition interval should be avoided by speed management and traffic education.
  Authors: Ni, Ying; Ling, Ziwen; Lin, Xiongfeng; Li, Keping
  Authors: Ni, Ying; Ling, Ziwen; Lin, Xiongfeng; Li, Keping
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3215
• Estimating Annual Average Daily Bicyclists: Error and Accuracy
  Abstract: Cities around the country are investing in bicycle infrastructure for which they seek to report bicycle use and safety improvements in order to secure additional transportation funding. A fundamental data need for performing safety studies and reporting facility use is bicyclist traffic volume. To address this need, manual bicycle counting programs have been established that count cyclists for a few hours per year at each designated location. A key issue that arises in designing counting programs (apart from the count locations) is the timing and frequency of the counts required to obtain a reliable estimate of annual average daily bicyclists (AADB). In particular, in which days of the week, hours of the day, and months of the year should counts be collected? And most important to the program cost, how many hours should be counted? This study uses continuous bicycle counts from Boulder, Colorado to estimate AADB and analyze the estimation errors that would be expected from various bicycle-counting scenarios. AADB average estimation errors were found to range from 15% with four weeks of continuous count data to 54% when only one hour is counted per year. This study recommends that counts be conducted for at least twenty-four hours, but perferrably for an entire week, using automated counting devices specificially calibrated for bicycle counting. Seasons with higher bicycle volumes have less variation in bicycle counts and thus more accurate estimates.
  Authors: Nordback, Krista; Marshall, Wesley; Janson, Bruce N.; Stolz, Elizabeth
  Authors: Nordback, Krista; Marshall, Wesley; Janson, Bruce N.; Stolz, Elizabeth
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists
  Session: 640
  Paper Number: 13-3281
• Traffic Flow Estimation Using Higher-Order Speed Statistics
  Abstract: In this article, we consider the problem of estimating traffic flow on a multi-lane road using a set of point speeds, either crowd-sourced or collected from the fixed infrastructure. We specifically investigate the relation between higher-order speed moments and the expected value of traffic flow. The algorithm proposed is based on the selection of optimal covariates constructed as speed moments, for a class of conditional mean predictors. The second contribution of this article consists in the analysis of specific components of the speed moments with significant correlation with flow values. In particular, we show that for more than 75\% of the fixed sensing devices considered, the correlation coefficient between the inter-lanes speed variance and the aggregate flow is more than 0.75. Additionally, for more than 70\% of these fixed sensing devices the lane speed variance increases with flow. The third contribution of this article consists of identifying the explanatory features for the high correlation between speed moments and flow values. The algorithms presented in this article are trained and tested on a large dataset from the Mobile Millennium system, collected in the Bay Area from August 2009 to October 2009.
  Authors: Bulteau, Edouard; Leblanc, Romain; Blandin, Sebastien; Bayen, Alexandre
  Authors: Bulteau, Edouard; Leblanc, Romain; Blandin, Sebastien; Bayen, Alexandre
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-3307
• Coupling Space Syntax with Network Equilibrium Model to Simulate Complex Pedestrian Flow in Transit Stations
  Abstract: The pedestrian comfort and safety level in mass transit stations is now attracting more and more attention, especially in many Asian cities, due to the congested pedestrian flow pattern. This pattern in stations is affected by factors such as the indoor spatial setting of the station, the traffic demand between the entrance and the stairs and the escalators. As a result, multi-directional pedestrian flows interact with each other and finally formed a relatively complex distribution. To simulate this kind of pedestrian flow for planning or evaluation, the present paper addresses two key models in the problem: a hybrid routing model and a collision avoidance model. Space syntax and network flow assignment is combined as a hybrid model to automatically construct pedestrian network and then assign pedestrian to different routes. This procedure provides pedestrians route information, i.e., a sequence of intermediate destinations. Meanwhile, a behavioral model is introduced during the pedestrian movement process to avoid collisions with each other and the obstacles as well. As a case study, a station flow scenario is at last simulated and discussed.
  Authors: Ma, Jian; Liu, Shaobo; Wang, Weili; Lo, S. M.
  Authors: Ma, Jian; Liu, Shaobo; Wang, Weili; Lo, S. M.
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-3322
• Conceptual Design for Research-Oriented, Web-Based Traffic Simulation Platform
  Abstract: Researchers rely on microscopic traffic simulation for highly detailed analysis. However, existing software packages either provide very less flexibility in modeling or require very extra proficiency in programming so as to evaluate a new technology or benchmark a novel behavior model. Therefore, a significant part of efforts in utilizing simulation tools is consumed on non-research related work. In this paper, we propose a new simulation software platform with more freedom in injecting customized models, friendlier graphic user interface, and automation in trivial but time-consuming work. To achieve those goals, several state-of-the-art software engineering structural design patterns are adopted. The critical part of the proposed platform is to separate the simulation engine and user interface on the two ends of the web. The core simulation is centralized at the server, and different research tasks, which are undertaken simultaneously, are distributed on the clients with Internet browsers. This paper presents the conceptual design of the software platform with illustration of the software engineering concepts underneath. A demonstration, employing the browser techniques to animate the traffic on an online map, is shown to verify the advantages.
  Authors: Shi, Xuan; Jin, Jing; Cheng, Yang; Parker, Steven; Zhang, Jian; Ran, Bin
  Authors: Shi, Xuan; Jin, Jing; Cheng, Yang; Parker, Steven; Zhang, Jian; Ran, Bin
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 283
  Paper Number: 13-3055
• Privacy Protection Method for Fine-Grained Urban Traffic Modeling Using Mobile Sensors
  Abstract: Privacy in transportation is controversial and under-studied. With the ubiquitous applications of Intelligent Transportation System (ITS) technologies, privacy issues in transportation are becoming increasingly important and need to be addressed carefully. As a well-known trade-off, data needs and privacy protection should be deliberately balanced for different applications. This paper focuses on developing privacy mechanisms to simultaneously satisfy privacy protection and modeling needs for fine-grained urban traffic modeling using mobile sensors. To accomplish this, a virtual trip lines (VTL) zone-based system and related filtering approaches are developed. Traffic-knowledge-based adversary models are proposed to evaluate the effectiveness of such system by making privacy attacks. The results show that besides ensuring an acceptable level of privacy, the released datasets from such privacy-enhancing system can also be applied to traffic applications with satisfactory performance. Albeit application specific, such “Privacy-by-Design” approach would hopefully shed some light on other applications.
  Authors: Sun, Zhanbo; Zan, Bin; Ban, Xuegang (Jeff); Gruteser, Marco
  Authors: Sun, Zhanbo; Zan, Bin; Ban, Xuegang (Jeff); Gruteser, Marco
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Policy
  Session: 325
  Paper Number: 13-3144
• Analyzing Different Functional Forms of the Varying Weight Parameter for Finite Mixture of Negative Binomial Regression Models
  Abstract: Previously, the weight parameter of the finite mixture of regression models has been assumed to be invariant of the characteristics of the observations under study. Recently, it has been shown that the weight parameter of the finite mixture of negative binomial (NB) models can be dependent upon the attributes of the sites. Since the selection of the functional form for weight parameter has a significant impact on the classification results, there is a need to investigate how different functional forms affect the estimation of the varying weight parameter and whether there is a common functional form that can be properly used to model the weight parameter for different crash datasets. The primary objective of this research is to investigate the effect of different functional forms on estimation of the weight parameter as well as the group classification. To accomplish the study objectives, ten different functional forms for the varying weight parameter were estimated using three different multilane rural highway segment datasets: Texas undivided data, Texas divided data and Washington divided data. The results of this study confirm that the selection of the functional form for weight parameter will affect the classification results significantly. Among ten different functional forms, one functional form stands out for the three datasets. Therefore, when using the finite mixture of NB models with varying weight parameters to analyze the crash data, it is suggested that transportation safety analysts should include Model 5 (which models the classification as a function of the segment length raised to a power) along with other alternative functional forms for describing the weight parameter and select the most appropriate functional form based on not only the goodness-of-fit statistics, but also the classification results.
  Authors: Zou, Yajie; Zhang, Yunlong; Lord, Dominique; Peng, Yichuan
  Authors: Zou, Yajie; Zhang, Yunlong; Lord, Dominique; Peng, Yichuan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-3929
• Allowing for Nonadditively Separable and Flexible Utility Forms in Multiple Discrete-Continuous Models
  Abstract: Many consumer choice situations are characterized by the simultaneous demand for multiple alternatives that are imperfect substitutes for one another, along with a continuous quantity dimension for each chosen alternative. To model such multiple discrete-continuous choices, most multiple discrete-continuous models in the literature use an additively-separable utility function, with the assumption that the marginal utility of one good is independent of the consumption of another good. In this paper, we develop model formulations for multiple discrete-continuous choices that allow a non-additive utility structure, and accommodate rich substitution structures and complementarity effects in the consumption patterns. Specifically, three different non-additive utility formulations are proposed based on alternative specifications and interpretations of stochasticity: (1) The deterministic utility random maximization (DU-RM) formulation, which considers stochasticity due to the random mistakes consumers make during utility maximization; (2) The random utility deterministic maximization (RU-DM) formulation, which considers stochasticity due to the analyst’s errors in characterizing the consumer’s utility function; and (3) The random utility random maximization (RU-RM) formulation, which considers both analyst’s errors and consumer’s mistakes within a unified framework. When applied to the consumer expenditure survey data in the United States, the proposed DU-RM and RD-DM non-additively separable utility formulations perform better than the additively separable counterparts, and suggest the presence of substitution and complementarity patterns in consumption.
  Authors: Bhat, Chandra R.; Castro, Marisol; Pinjari, Abdul Rawoof
  Authors: Bhat, Chandra R.; Castro, Marisol; Pinjari, Abdul Rawoof
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4076
• Assessment of the Degree of Willingness to Change from Motorized Travel Modes to Walking or Cycling
  Abstract: This paper presents an analysis of the degree of willingness to change from motorized travel modes to walking or cycling. Information was collected in a novel data collection effort based on multiple survey methods. Firstly, respondents traveling by car or transit were asked about their willingness to change to walking or cycling. Secondly, those willing to change participated in a stated tolerance survey to identify the improvement measures required to change. Lastly, a hypothetical scenario was presented to respondents in which previously selected improvement measures were implemented and they were supposed to be cycling or walking. In this last scenario, gradual reductions in travel costs of their usual motorized travel mode were presented until they gave up cycling or walking. Those decided to keep on walking or cycling in this scenario are assumed to have a strong willingness to change, in contrast with those who decided to come back to their usual motorized travel mode. The degree of willingness to change estimated using this methodology would reduce uncertainty about the difference between stated willingness to change and real shifts from car or ransit to non-motorized transportation modes.Results from a statistical analysis carried out using Heckman’s sample selection model allow us to identify demographic, socioeconomic and travel-related factors that influence the degree of willingness to change. Differences and similarities between the propensity to walk and cycle and between individuals with strong and weak willingness to change are underlined. Findings suggest that work/school related journeys are less associated to walking than non-commuting journeys, but they are more related to cycling. Results provided by the analysis of the degree of willingness reveal that car users present a stronger willingness to change to walking or cycling compared to transit users. In addition, older respondents show a stronger willingness to switch to walking or cycling than younger respondents.
  Authors: Ferrer, Sheila; Ruiz, Tomás
  Authors: Ferrer, Sheila; Ruiz, Tomás
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4088
• Evaluating Alternate Discrete Choice Frameworks for Modeling Crash Injury Severity
  Abstract: This paper focuses on the relevance of alternate discrete choice frameworks for modeling driver injury severity. The study empirically compares the ordered response and unordered response models in the context of driver injury severity in traffic crashes. The alternative modeling approaches considered for the comparison exercise include: for the ordered response framework- ordered logit (OL), generalized ordered logit (GOL) and for the unordered response framework - multinomial logit (MNL), nested logit (NL) and ordered generalized extreme value logit (OGEV) model. A host of comparison metrics are computed to evaluate the performance of these alternative models. To our knowledge, the study provides a first of its kind comparison exercise of the performance of ordered and unordered response models for examining the impact of exogenous factors on the driver injury severity. The research also captures the effect of potential underreporting on alternative choice frameworks by artificially creating an underreported data sample from the driver injury severity sample.The empirical analysis is based on the 2010 General Estimates System (GES) data base. The comparison exercise clearly highlights the superiority of the GOL model on the estimation and the validation sample in terms of data fit compared to the OL and MNL models. The estimation with the artificial underreported sample consistently obtains the wrong elasticities and these errors are substantially reduced for both GOL and MNL models with the correction measures for the thresholds/constants of these models based on the true aggregate shares. The most striking finding is the fact that the MNL model does not perform any better in the underreporting context. In fact, the GOL elasticity effects of underreported estimates with corrections are closer to the true elasticity effects than that of the MNL model. Overall, the results of the empirical comparison provide credence to the belief that an ordered systems that allow for exogenous variable effects to vary across alternatives offer superior fit compared to unordered systems in modeling driver injury severity.
  Authors: Yasmin, Shamsunnahar; Eluru, Naveen
  Authors: Yasmin, Shamsunnahar; Eluru, Naveen
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-4081
• Enhanced Analysis of Crashes in the Proximity of Work Zones Through Integration of Statewide Crash Data with Lane Closure System Data
  Abstract: Highway work zones interrupt regular traffic flow and lead to safety concerns. Comprehensive knowledge of the crashes and work zones is essential to identify the risk factors. The Wisconsin Lane Closure System (WisLCS), a scheduling and reporting system for highway lane closures statewide, provides a new opportunity to match crashes to specific work zones on a system-wide level. This study conducts an analysis of the safety risks in the proximity of work zones. The WisLCS and the MV4000 Crash Data Retrieval Facility, both part of the WisTransProtal system at the University of Wisconsin-Madison TOPS Laboratory, provide the necessary data for this study. A matching algorithm is used to relate reported work zone crashes with the corresponding work zones, which relies on a common underlying linear referencing system used in the two data systems. Based on the results, it is clear that work zones cause safety concerns outside of the physical boundaries (upstream and downstream) and scheduled time periods (before and after the reported operation hours). In some scenarios, those crashes occurring outside of work zones even have a higher risk of overall and severer injury. Some suggestions are also made based on the findings to improve work zone safety and enhance work zone reporting monitoring in the future. Although developed based on the systems in Wisconsin, the general ideas of this study can also be applied to similar information systems.
  Authors: Cheng, Yang; Parker, Steven; Ran, Bin; Noyce, David A.; Szymkowski, Rebecca
  Authors: Cheng, Yang; Parker, Steven; Ran, Bin; Noyce, David A.; Szymkowski, Rebecca
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 423
  Paper Number: 13-3359
• Computational Model for Stop-Start Wave Propagation Velocity Estimation Based on Unmanned Aerial Vehicle
  Abstract: The parameters involved in current traffic wave theoretical models such as the smooth relationship between velocity and density are difficult to obtain through traditional traffic detection devices, so it is difficult to apply these theoretical models to the actual verification and prediction for real situation. This paper investigates modeling of propagation velocity of stop-start wave at signalized intersections. Unmanned aerial vehicle (UAV) is introduced in this study as a new type of traffic information collection method to gather the real-time data of the necessary parameters which can hardly be obtained by traditional traffic detection devices. The influencing factors of the stop-start wave in actual situations such as traffic density in the queuing state and the proportion taken by large and medium-sized vehicles in the traffic are analyzed based on the traffic wave theory. Using them as the basic parameters, a computational model is developed to model the stop-start wave propagation velocity. A verification experiment is taken at the intersection of the Cao-an Highway and North Jia-song Road in Shanghai, China. Wave speeds calculated from the computational model of several cases are compared with the real wave speeds derived from actual observations using UAV. Data validation shows that this computational model fits well with the observation.
  Authors: Cheng, Ke; Chang, Yuntao; Peng, Zhong-Ren
  Authors: Cheng, Ke; Chang, Yuntao; Peng, Zhong-Ren
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-3472
• Model-Free Networks as Basis for Transport Data Hub
  Abstract: Transport applications usually require a network description to map collecteddata, to simulate traffic, or to analyze routing or traffic demand spreading through anarea. Many applications are developed to support these tasks, and all of them are using adifferent network definition and require different input files. This leads to a lot ofredundancy in data storage, fragmented data availability, and problems in dataacquisition. This paper introduces a model free network standard that is able to cater forthe needs of various applications, and build a solid basis for a transport data hub, whichcould be utilized as a single source of data access for road authorities. The standard hasbeen integrated with a research framework for simulation, a commercial simulationpackage, and a visualization tool to demonstrate its potential.
  Authors: Miska, Marc Philipp; Nantes, Alfredo; Torday, Alexandre; Jin, Han; Chung, Edward
  Authors: Miska, Marc Philipp; Nantes, Alfredo; Torday, Alexandre; Jin, Han; Chung, Edward
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 283
  Paper Number: 13-3481
• Route Choice Dynamics After a Link Restoration
  Abstract: Carrion and Levinson (2012a) studied the bridge choice behavior of commuters before and after a new bridge opened to the public. This bridge replaced the previously collapsed I-35W bridge in the metro area of Minneapolis-St. Paul. The original I-35W bridge collapsed on August 1st 2007, and the replacement bridge opened to the public on September 18th 2008. They collected Global Positioning System (GPS) data of travelers between the last weeks of August 2008, and the first weeks of December 2008. This data allowed to observe the traffic patterns of the travelers on the road network, and identify the possible reasons influencing the travelers' preferences towards the new I-35W bridge vs. other bridge alternatives. For this purpose, they formulated a static model based on statistical measures (e.g. mean, standard deviation) on day-to-day travel time distributions obtained by aggregating travel times of different days for the I-35W bridge, and for all the other alternatives. This study extends Carrion and Levinson (2012a) by considering explicitly the day-to-day behavior of travelers, and by also considering the previously excluded subjects that are transitioning between bridge alternatives not including the I-35W bridge. This is accomplished by specifying and estimating a duration model (i.e. a hazard model) on data of the subjects' morning commute. The primary results indicate that the subjects react to day-to-day travel times on a specific route according to thresholds. These thresholds help discriminate whether a travel time is within an acceptable margin or not, and travelers may decide to abandon the chosen route depending on the frequency of travel times within acceptable margins. The secondary results indicate that subjects previous experience, and perception of the alternatives also influence their decision to abandon the chosen route.
  Authors: Carrion, Carlos; Levinson, David M.
  Authors: Carrion, Carlos; Levinson, David M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-3483
• Nested Tourist Time Use and Expenditure Behavior Model with Multidestination Visit Based on Pair Copula
  Abstract: Focusing on tourist behavior, this paper develops a nested time use and expenditure behavior model in the context of multi-destination visit, where a tourist visits one or more destinations. In this case, tourists' decisions include, 1) whether to visit a destination or not (destination visit decision), and in case of visiting a destination, 2) how long to stay there (activity time decision), 3) whether to spend any money there (expenditure decision), and in case of spending any money, 4) how much of money to spend there (expenditure level decision). To accommodate the above decision-making mechanism with two discrete and two continuous dependent variables, a nested Tobit modeling technique is first integrated with a multi-linear utility-maximizing time use and expenditure behavior model, and then a pair copula is applied to represent the correlated error structure of the above four dependent variables. Pair copula is a function that can combine different bivariate copulas to represent a joint multivariate distribution, where variables are sequentially incorporated into conditioning sets with a nested tree structure. As a case study, the developed model is estimated by comparing three types of canonical vine copulas: Gaussian, FGM and Frank copulas. First, the model effectiveness is confirmed by using a questionnaire data collected in the Tottori Prefecture of Japan in 2007. Second, it is revealed that the Frank canonical vine pair copula model is superior to other models. Third, it is found that the value of activity time varies considerably with touristsf origins. Finally, influential factors to time use and expenditure behavior are examined.
  Authors: Zhang, Hui; Zhang, Junyi
  Authors: Zhang, Hui; Zhang, Junyi
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-3513
• Value-of-Time Multipliers: Review and Meta-analysis of European-wide Evidence
  Abstract: This paper is different in that it provides a review of time multipliers in contrast to the much more common reviews of monetary values. There are a number of attractions of analysing what are essentially within-study valuations of the time related attributes expressed in equivalent units of in-vehicle time rather than deducing the multipliers from analysis of more disparate monetary valuations. We here provide the most comprehensive review of time multiplier evidence yet conducted, covering 12 attributes on a European wide scale. We have assembled 1389 multipliers drawn from 244 studies and covering 18 European countries and have estimated a model to explain variations in these multipliers as a function of a large number of candidate explanatory variables. The multipliers considered are walk and wait time, access to public transport and waiting at interchange locations, time spent searching for a parking space and in congested traffic conditions, departure time shift, headway, schedule delay early and late, the standard deviation of travel time and late time. The main influences on the time multipliers are journey distance, mode and journey purpose. Whilst we observe quite appreciable but plausible variations in some multipliers across contexts, the variation is less than is observed in reviews of monetary valuations. The results seem to be transferable across Europe and will provide a valuable resource, not least in allowing money values of a range of attributes to be deduced from the more widely available money values of in-vehicle time.
  Authors: Wardman, Mark
  Authors: Wardman, Mark
  Year: 2013
  Document Type: Paper
  Subject: International Activities; Data and Information Technology; Planning and Forecasting
  Session: 819
  Paper Number: 13-3554
• Robust Method for Real-Time Estimation of Travel Times for Dense Urban Road Networks Using Point-to-Point Detectors
  Abstract: The collection and provision of real time information to passengers is a key issue on current cities for both, traffic managers and travelers. This paper presents a novel methodology for estimating travel times in dense urban road networks using point-to-point detectors. The aim is to fill in the existing gap related to the weakness of existing travel time estimation methodologies, which take into account point-to-point detector devices. Bluetooth is considered as one of the less expensive technologies for estimating travel times, but while on the one hand travel times data collection can be considered as easy, data filtering and data correction require a demanding methodology, which if not correctly applied may result in inaccurate results as compared to other methods. The main difficulty of data processing is to identify the correct set of MAC addresses for estimating the travel times, especially in dense urban zones, where three main error sources exist: the existence of different modes (private vehicles, pedestrians, buses, bicycle etc.), the existence of more than one possible path between two bluetooth detector devices and the existence of stops or trips ending between two bluetooth devices, creating outliers that need to be identified and discarded. The results of the methodology confirm that outliers are eliminated, as shown by a case study involving 10 Bluetooth detectors, installed at major intersections of Thessaloniki’s central business district. The presented methodology is useful for application related to real-time data provision to advanced traveler information services as well as to underlying traffic models.
  Authors: Mitsakis, Evangelos; Salanova Grau, Josep-Maria; Chrisohoou, Evangelia Ch.; Aifadopoulou, Georgia
  Authors: Mitsakis, Evangelos; Salanova Grau, Josep-Maria; Chrisohoou, Evangelia Ch.; Aifadopoulou, Georgia
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3654
• Framework to Evaluate Rescheduling due to Unexpected Events in an Activity-Based Model
  Abstract: The concept of rescheduling is essential to activity-based modeling in order to calculate effects of both unexpected incidents and adaptation of individuals to traffic demand management measures. When collaboration between individuals is involved or timetable based public transportation modes are chosen, rescheduling becomes complex. This paper describes a new framework to investigate algorithms for rescheduling on a large scale. The framework explicitely models the information flow between traffic information services and travelers. It combines macroscopic traffic assignment with microscopic simulation of agents adapting their schedules. Perception filtering is introduced to allow for traveler specific interpretation of perceived macroscopic data and information going unnoticed; it feeds person specific short term predictions required for schedule adaptation. Individuals are assumed to maximize schedule utility. Initial agendas are created by the FEATHERS activity-based schedule generator for mutually independent individuals using an undisturbed loaded transportation network. The new framework allows both agent behavior and external phenomena to influence the transportation network state; individuals interpret the state changes via perception filtering and start adapting their schedules, again affecting the network via updated traffic demand. The first rescheduler investigated uses marginal utility that monotonically decreases with activity duration and a monotonically converging relaxation algorithm to efficiently determine the new activity timing. The current framework implementation can support re-timing, re-location and activity re-sequencing; re-routing however is the subject of future research.
  Authors: Knapen, Luk; Usman, Muhammad; Yasar, Ansar-Ul-Haque; Bellemans, Tom; Janssens, Davy; Wets, Geert
  Authors: Knapen, Luk; Usman, Muhammad; Yasar, Ansar-Ul-Haque; Bellemans, Tom; Janssens, Davy; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-3682
• Estimating Dynamic Workplace Capacities Using Public Transport Smart Card Data, Travel Diary Survey, and Land Use Information
  Abstract: The number and spatial distribution of work locations is a crucial piece of information for any transport demand model. To generate the initial transport demand of MATSim, an activity-based multi-agent simulation framework, it is necessary to determine the number of work locations with high spatial resolution, either on a parcel or even a building level. Commonly applied methods to derive work locations are based on census of entreprises information, unemployment insurance database or combine information of buildings gross floor area and individual work space requirements. As an alternative, we present a methodology which combines public transport smart card transaction data, travel diary survey and building information data sources.Work activities are detected from public transport smart card transactions based on observed activity duration and start time and hence related to public transport stops. To link the observed work activities to individual buildings, a linear programming optimisation technique is applied that minimises the walking time between public transport stops and potential work locations. Information on maximum allowed building gross floor area derived from land use regulation is combined with estimates on individual work space requirements to set boundary conditions and ensure that buildings are only assigned with work activities according to its maximal capacity. To account for private transport based work activities, mode shares as observed in a travel diary are taken into account. Due to the limited number of observations of such surveys, this inflation process is performed on the level of specifically generated mode share zones. To demonstrate the applicability, the proposed approach is implemented for the case of Singapore and the results of this case study critically reviewed.
  Authors: Ordóñez Medina, Sergio; Erath, Alexander
  Authors: Ordóñez Medina, Sergio; Erath, Alexander
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3683
• Evaluating Short-Term Traffic Volume Forecasting Models Based on Multiple Data Sets and Data Diagnosis Measures
  Abstract: Although several short-term traffic volume forecasting methods have recently been developed, there is currently a lack of the studies which focus on how to choose the appropriate prediction method based on the statistical characteristics of the dataset. This paper first diagnoses the predictability of four different traffic volume datasets using various statistical measures including: (1) complexity analysis methods such as the delay time and embedding dimension method and the approximate entropy method; (2) nonlinearity analysis methods like the time reversibility of surrogate data; and (3) long range dependency analysis techniques like the Hurst Exponent. Following the diagnosis of the datasets, three short term traffic volume prediction models are applied: (1) Seasonal Autoregressive Integrated Moving Average (SARIMA); (2) k Nearest Neighbor (k-NN); and (3) Support Vector Regression (SVR). The results from the statistical data diagnosis methods are then correlated to the performance results of the three prediction methods on the four datasets in order to arrive at some conclusions regarding how to choose the appropriate prediction method. Among the conclusions of the study in that regard is that SVR is more suitable for nonlinear datasets, while SARIMA and k-NN are more appropriate for linear datasets. The data diagnosis results are also utilized to shed light on how to select the parameters of the different prediction models such as the length of the training data set for SARIMA and SVR, the average number of nearest neighbors for k-NN, and the input vector length for k-NN and SVR. Key Words: Short-term traffic volume prediction; time series analysis; Seasonal Autoregressive Integrated Moving Average (SARIMA); k Nearest Neighbor (k-NN); Support Vector Regression (SVR); Statistical methods
  Authors: Lin, Lei; Wang, Qian; Sadek, Adel W.
  Authors: Lin, Lei; Wang, Qian; Sadek, Adel W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-3691
• Identifying and Classifying Freight Trip Stops from GPS Data
  Abstract: Many previous efforts have been made to use global positioning system (GPS) data gathered from mobile units to measure freight network performance. While the majority of these previous works were instrumental in establishing the technical reliability of GPS information and using that information to measure basic network performance, there have been few if any attempts to classify stops (i.e. stops for deliveries, unscheduled stops and traffic stops). Using data from freight vehicles in the New York City metropolitan area we developed a three step process to identify and classify trip stops by purpose (i.e. rest stops, unscheduled, deliveries) and calculate the relevant tour performance measures such as average delivery stops per tour, average service time and vehicle movements per destination.
  Authors: Richardson, Eric; Ban, Xuegang (Jeff); Holguín-Veras, Jose
  Authors: Richardson, Eric; Ban, Xuegang (Jeff); Holguín-Veras, Jose
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Freight Transportation
  Session: 410
  Paper Number: 13-3737
• Freeway Travel Time Information in Real Time: New Opportunity for Spot Speed Methods
  Abstract: This paper shows that the precision of a freeway travel time information system, in a real-time context, is not related solely to the accuracy of the measurement. Immediacy in reporting the information and forecasting capabilities play a role. Therefore, focusing only on the accuracy of the travel time measurement is a myopic approach, which can lead to counterintuitive results.Specifically, it is claimed that using travel times estimated with the traditional spot speed Midpoint algorithm, the performance of the real-time information system is better than by using much more accurate directly measured travel times. Guidelines for an adequate configuration of the common parameters of the system are provided. These are addressed by taking into account an easy and practical implementation. They have been proven to work well in an empirical application on a Spanish Freeway.
  Authors: Soriguera, Francesc
  Authors: Soriguera, Francesc
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 766
  Paper Number: 13-3743
• Within-Individual Variation in Preferences: Equity Effects of Congestion Charges
  Abstract: It is widely recognized that congestion pricing could be an effective measure to solve congestion problems in urban areas. Still, congestion pricing has been implemented in few places possibly because of the notion that it has negative equity effects. But, earlier studies on equity effects of road pricing have disregarded the possibility that preferences might vary between different trips for the same individual. The purpose of this research is to study how the value of time and preferences for different modes varies within individuals as compared to the variation between individuals. Using a a six weeks period revelead preference panel data and the stated preference for a mode choice context, both collected in Switzerland, a mixed revealed/stated preference logit mode choice model was estimated and used to simulate how the value of travel time savings (VTTS) varies across trips within and between individuals over the six weeks period. We found that the variation in VTTS dependent on income is smaller than the variation within individuals, and the variation in loss per trip due to a simple and hypothetical congestion charging scheme (before recycling of the money) is about twice as high if not taking into account of the intra-individual variation of VTTS. However, the fact that some individuals make more trips than others seems to have a larger effect on the redistribution of losses. To quantify the role of intra-individual variation VTTS is important and might brush aside or reaffirm the conception that congestion charges have negative equity effects.
  Authors: Börjesson, Maria Magdalena; Cherchi, Elisabetta; Bierlaire, Michel
  Authors: Börjesson, Maria Magdalena; Cherchi, Elisabetta; Bierlaire, Michel
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-3749
• Hierarchical Agent-Based Simulation for Modeling Traveler Behavior
  Abstract: Understanding traveler behaviors is very important in studying the transportation system. Traveler behaviors can be divided into two parts: before a trip and within a trip. In this paper, the before trip behavior mainly refers to route choice and the within trip behavior includes tactical driving which may include free-flow driving, car following and lane changing. The route choice and the tactical driving behavior may change as time elapses due to the interactions between travelers as well as due to changes in the transportation network topology. This paper proposes a hierarchical agent-based simulation framework with route choice behavior on the upper level and tactical driving behavior on the lower level and includes travelers’ interactions with the transportation network. The route choice model considers learning from previous experiences, heterogeneity of different travelers, incomplete network information, and communications between travelers. The tactical driving model is mainly derived from the NGSIM program. This hierarchical framework is implemented in AnyLogic® software and tested with two simulation experiments. Results from numeric examples show that the proposed agent models reach the same equilibrium solutions as reported in classical models in the literature and how network topology changes can influence the traveler’s decision making. This agent based modeling paradigm opens the possibility to study and understand the complexity travelers’ decision making under a wide variety of scenarios.
  Authors: Feng, Yiheng; Head, Larry
  Authors: Feng, Yiheng; Head, Larry
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-4169
• Analysis of Adaptive Data Fusion Algorithm for Urban Network Application
  Abstract: Due to the development in sensing and communication technology, urban traffic data become increasingly available. This provides excellent opportunity for detailed research on urban traffic flow. The challenge is how to make the best use of these newly available data. This paper analyses the use of different type of data for retrieving the underlying traffic pattern. We present and investigate a data fusion algorithm for integrating heterogeneous traffic data in urban networks. The fusion algorithm is developed based upon the adaptive smoothing method (ASM) proposed by Treiber and Helbing. The objective is to produce a more refined picture of urban traffic through processing and integrating data from different sources in urban network. The filtering and fusion algorithm can work with data collected in different spatio-temporal granularity, with different level of accuracy, and from different kinds of sensors. The accuracy of the fusion algorithm is evaluated on a VISSIM microscopic simulation test-bed. This paper contributes to urban traffic analysis and management.
  Authors: Chow, Andy H. F.; Scarinci, Riccardo; Heydecker, Benjamin G.
  Authors: Chow, Andy H. F.; Scarinci, Riccardo; Heydecker, Benjamin G.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-4189
• Simultaneous Analysis of Global Decisions in Activity-TravelScheduling Process
  Abstract: This paper presents a global characterization of activity-travel scheduling decisions using a new dataset recently collected in Valencia (Spain). As an innovative approach, bivariate probit sample selection models are used to take into account potential self-selectivity bias in the decision process. Model 1 studies decisions to realize or not activity-travel episodes considering if they have been included in the pre-planned agenda. Model 2 analyzes decisions to perform activity-travel episodes as they were planned or to modify one or more of their attributes prior to execution, considering if they have been decided to be realized previously. Random parameters are used in both models to accommodate heterogeneity effects.Location, timing and duration of activity-travel episodes are important explanatory variables in the two scheduling process studied. Few demographic and socioeconomic variables affect the decision processes. Significant correlations between decisions included in both models are found. Policy implications of the analysis results are highlighted.
  Authors: Garcia-Garces, Pablo; Ruiz, Tomás
  Authors: Garcia-Garces, Pablo; Ruiz, Tomás
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4194
• Understanding and Estimating Travelers’ Choices Toward International Multimodal Journey Planning
  Abstract: This paper reports the outcomes of empirical research into international multimodal travel choices, executed within the Enhanced WISETRIP project (EU Funded FP7 Framework Research Program). The project aims at developing new possibilities for planning, booking and travelling multimodal international journeys adapted to user needs, multiple trip criteria, and environmental impact. Crucial for achieving the project’s ambitious goal, is to be able to capture a wide-range of user needs and diverse journeys, for which a so-called a ‘trip strategy’ is defined. A “Techno-Experiential Design Assessment” (TEDA), comprising of user interviews and a stated preference survey, was designed and implemented. The analysis of the TEDA outcomes has resulted in rules and constraints for the trip strategy. The trip strategy modeling considers personalized choice criteria and representative travel situations based on forecasts or user defined possibilities of events. Five group interviews, including trials on user experience with potential scenarios and alternative presentations of travel information, were conducted. After that two online stated preference surveys were carried out for four distance classes for international travelers. The outcomes of the interviews and survey include some interesting findings: (1) majority of travelers indicate the need for a multimodal tip planner; (2) use of real-time information and disruption messaging is doubled when roaming cost is not an issue; (3) travelers are willing to switch to more CO2 friendly route if all other items are comparable; (4) safety, comfort and cost are the most important factors that determine the modal and itinerary choice. These practical results help in a better understanding and are considered critical in achieving an enhanced international multimodal journey planner that should be affordable and encouraging for a wide variety of users.
  Authors: Chen, Yusen; Jonkers, Eline; Vonk Noordegraaf, Diana
  Authors: Chen, Yusen; Jonkers, Eline; Vonk Noordegraaf, Diana
  Year: 2013
  Document Type: Paper
  Subject: International Activities; Data and Information Technology; Planning and Forecasting
  Session: 819
  Paper Number: 13-4213
• Dynamic Autoregressive Neural Networks for Spatially Distributed Time Series Prediction of Car Crashes in Urban Networks
  Abstract: Following the public and administrative concern on road safety that is evident in the last decades a significant effort has been done for surveying, modelling and predicting road accidents. One of the important aspects for optimal planning and scheduling of road safety resources stands for the prediction models. The majority of the existing models are aiming either on correlating traffic variables with crash occurrence or modelling crash frequencies both in highways as well in urban network links and intersections. In the current paper, results from an exploratory analysis are presenting, based on spatially distributed time series prediction modelling, belonging to the Artificial Intelligent class of modelling approaches. Such approach in road safety is not widely presented in the literature although can be regarded as useful in cases where detailed and reliable information of traffic characteristics is not available. In particular, the performance of Artificial Intelligent-based predictors is investigated. A suitable for such analysis realistic database (composed of daily records covering almost 6 years) from Riyadh, capital of the Kingdom of Saudi Arabia is analyzed by a hybrid dynamic Autoregressive Artificial Neural Network setup, providing evidence on the performance of such approaches in predicting spatially distributed car crashes time series.
  Authors: Dimitriou, Loukas; Hassan, Hany M.
  Authors: Dimitriou, Loukas; Hassan, Hany M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 482
  Paper Number: 13-4272
• Development of Indicator to Assess Spatial Fit of Discrete Choice Models
  Abstract: Discrete choice models are increasingly implemented using geographical data. When this is the case, it may not be sufficient to project market shares accurately, but also to correctly locate them in space. Analysts might then be interested in assessing the results of a model’s fit relative to the spatial distribution of the observed responses. While canonical approaches exist for the exploratory spatial analysis of continuous variables, similar tools have not been widely implemented for discrete choice models, where the variable of interest is qualitative. For this reason, despite recent progress with spatial models for discrete outcomes, there is still not a simple and intuitive tool to assess the quality of the spatial fit of a discrete choice model. The objective of this paper is to introduce a new indicator of spatial fit that can be applied to the results of discrete choice models. Use of the indicator is demonstrated by means of a case study of vehicle ownership in Montreal, Canada.
  Authors: Paez, Antonio; Lopez, Fernando; Ruiz, Manuel; Morency, Catherine
  Authors: Paez, Antonio; Lopez, Fernando; Ruiz, Manuel; Morency, Catherine
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4290
• Screening Naturalistic Driving Study Data
  Abstract: This study responds to the need to screen events observed during naturalistic driving studies to derive a set of crashes and near crashes with common etiologies; referred to as well-defined surrogate events. Two factors are critical to the identification of these well- defined surrogate events: selection of screening criteria and the designation of a time window to be used for event search. This paper describes testing conducted using an algorithm developed in a previous paper (Wu and Jovanis, 2011b). The algorithm allows for the use of a range of search criteria to identify events with common etiology from raw naturalistic driving data. A range of kinematic search criteria are used to screen events including lateral and longitudinal accelerations averaged over different time windows and characterized by average as well as maximum values during a time window. The testing is conducted using data from road departure events collected during a concluded 100-car naturalistic driving study. A total of 51 non-intersection and 12 intersection-related run-off-road events are included in the testing. Different sets of events were identified using different search criteria with different time windows. Diagnostic tools borrowed from medicine identify the best screening criteria and time windows. The methods allow for enhanced identification of well-defined surrogates using covariates such as driver attributes context and driver fatigue. The research illustrates a flexible procedure using a variety of statistical methods that are shown to effectively screen crashes and near crashes.
  Authors: Wu, Kun-Feng; Jovanis, Paul P.
  Authors: Wu, Kun-Feng; Jovanis, Paul P.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4293
• Ethical and Legal Issues Relating to Government Agencies and Intelligent Transportation Systems Data
  Abstract: The convergence of sensing, wireless telecommunications, and multi-media platforms have provided new opportunities for the development of intelligent transportation systems (ITS). These systems can provide real-time information to travelers and transportation agencies. As well as increase the overall efficiency and improve the management of the transportation network. While ITS applications, including those derived from connected vehicle technology, can enhance mobility, increase safety, and improve the environmental performance of the transportation system, they also raise legal and ethical questions about privacy, anonymity, and other concerns related to use of ITS data. As a prerequisite to deployment of ITS technologies, issues regarding the collection, management, and use of data must be addressed to the satisfaction of all parties, including government agencies, businesses, and private citizens. This paper summarizes the legal environment surrounding ITS, as well as controls used by agencies and industry to ensure ethical practices relating to ITS. Next, it describes specific ITS applications and discusses several issues relating to government involvement with ITS applications and data. Finally, the paper outlines specific recommendations for ITS planners and developers. These recommendations address determining system attributes and requirements while considering ethical implications and tradeoffs; resolving acceptance, adoption, and equity issues; and designing a system for the ethical governance and management of ITS and the information they create.
  Authors: Wallace, Richard; Hong, Qiang
  Authors: Wallace, Richard; Hong, Qiang
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Policy
  Session: 325
  Paper Number: 13-4295
• Standardized Data Processing: Where We Need It in Mining Private-Sector Probe-Based Traffic Data for Highway Performance Measurement
  Abstract: Reporting highway performance regarding congestion and reliability is required by the newly enacted transportation law of the United States – MAP-21. With unprecedented coverage and details, the private sector probe-based traffic data is among the most promising sources to establish a highway performance monitoring system that can track congestion and reliability on a national scale. But having the data itself is not enough – there are many variants in the data and data processing procedures that can result in significantly different results even based on the same set of data. As demonstrated in this paper, the space mean speed feature of probe data, segment location referencing, different data archiving frequencies, different calculation procedures, and the difference between experienced travel time and instantaneous travel time could all play a role in determining the values of certain performance measures. Standardized data elements and data processing procedures should be established in the effort of using proprietary probe data for highway performance measurement.
  Authors: Pu, Wenjing
  Authors: Pu, Wenjing
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 766
  Paper Number: 13-4242
• Surveying Hard-to-Reach Groups: Is a Cell Phone Survey the Solution?
  Abstract: Montreal’s Origin-Destination (O-D) surveys have traditionally used residential telephone listings as a sample frame. The population covered by these lists was estimated at around 90% in 2002; however the increase of cell-phone-only households has eroded its coverage. A direct consequence of this technological shift is the increasing difficulty in reaching young people aged 20 to 34 and single-person households; it is estimated half of 20 to 34 year olds reside in a cell-phone-only household. In March 2012, 464 surveys were completed with cell-phone-only households as part of the continuous O-D travel survey. 56% of respondents of the cell-phone-only sample were in the 20-to-34 age bracket. Differences exist between both samples; cell-phone-only households own fewer cars, have lower incomes, are more likely to live in central neighborhoods and are less likely to have children under 15 living in them. However, when comparing two sub-samples with the same characteristics, no significant differences were found, except the average number of cars per household and the proportion of households with a lower household income. Challenges in surveying cell-phone-only households include the impossibility of controlling the sample geographically until after the survey has begun and its high costs; each completed survey costs 3 times as much as one completed using the landline sample.
  Authors: Cerda, Assumpta
  Authors: Cerda, Assumpta
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-4327
• Urban Traffic State Estimation for Signal Control UsingMixed Data Sources and Extended Kalman Filter
  Abstract: This paper describes a methodology for fusing data from multiple sensors, including wireless de-vices and inductive loops, to make an estimation of the instantaneous state of an urban trafficnetwork. An extended Kalman filter is employed along with a state evolution model to make es-timates of the state in a discretized network. The instantaneous state is an estimate of the currentdistribution of vehicles in the network and their instantaneous speeds. Microsimulation tests wereused to evaluate the performance of the state estimation on a small urban networks. These resultsindicate low error between the estimated state and the known ground truth.
  Authors: Box, Simon
  Authors: Box, Simon
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 530
  Paper Number: 13-4310
• The Magnitude of the Regression to the Mean Effect in Traffic Crashes
  Abstract: Regression to the mean has been recognized as a phenomenon that influences road safety evaluations and should be accounted for. However, some doubts have risen about the necessity to implement rather sophisticated techniques such as the Empirical Bayes method to correct for regression to the mean whereas the use of a sufficient long before-period could reach the same objective. Present study examines the existence and the magnitude of the regression to the mean effect in crash data from 169 intersections in Flanders-Belgium for whom regression to the mean was likely to occur as they were selected based on their crash history. The presence of a RTM-effect was investigated by comparing the crash numbers of this period with the crash numbers in the next three years, during which no traffic safety measure was applied. Two comparison groups were used. The results demonstrate the existence of a substantial regression to the mean effect in the investigated sample of intersections. The magnitude of the regression to the mean effect is estimated to be almost 9% for injury crashes and 37% for the most severe crashes. It is concluded that the Empirical Bayes method effectively corrects for regression to the mean. Correction for regression to the mean in evaluation studies is highly recommended in cases when locations are selected based on their crash history.
  Authors: De Pauw, Ellen; Daniels, Stijn; Brijs, Tom; Hermans, Elke; Wets, Geert
  Authors: De Pauw, Ellen; Daniels, Stijn; Brijs, Tom; Hermans, Elke; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3772
• Spatial Generalized Ordered-Response Model to Examine Highway Crash Injury Severity
  Abstract: This paper proposes a flexible econometric structure for injury severity analysis at the level of individual crashes that recognizes the ordinal nature of injury severity categories, allows unobserved heterogeneity in the effects of contributing factors, as well as accommodates spatial dependencies in the injury severity levels experienced in crashes that occur close to one another in space. The modeling framework is applied to analyze the injury severity sustained in crashes occurring on highway road segments in Austin, Texas. The results from our analysis underscore the value of our proposed model to accurately estimate variable effects.
  Authors: Castro, Marisol; Paleti, Rajesh; Bhat, Chandra R.
  Authors: Castro, Marisol; Paleti, Rajesh; Bhat, Chandra R.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-3810
• Joint Analysis of Injury Severity of Drivers in Two-Vehicle Crashes Accommodating Seat Belt Use Endogeneity
  Abstract: The current study contributes to the existing injury severity modeling literature by developing a multivariate probit model of injury severity and seat belt use decisions of both drivers involved in two-vehicle crashes. The modeling approach enables the joint modeling of the injury severity of multiple individuals involved in a crash, while also recognizing the endogeneity of seat belt use in predicting injury severity levels as well as accommodating unobserved heterogeneity in the effects of variables. The proposed model is applied to analyze the injury severity of drivers involved in two-vehicle road crashes in Denmark.
  Authors: Abay, Kibrom A.; Paleti, Rajesh; Bhat, Chandra R.
  Authors: Abay, Kibrom A.; Paleti, Rajesh; Bhat, Chandra R.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3845
• Exploration of Data-Pooling Techniques: Modeling Activity Participation and Household Technology Holdings
  Abstract: As data collection costs escalate and travel behaviour models become more data hungry, it becomes increasingly important to exploit existing sources of data to the greatest extent possible. Data fusion as a means of combining disparate sources of data, collected from entirely unconnected surveys, is therefore an avenue worth exploring. In this paper, we explore the possibility of pooling data from the UK National Travel Survey (NTS) and the UK Time Use Survey (TUS) to model the impacts of household technology holdings on leisure activity participation. We test three different data pooling techniques: ad-hoc cluster sampling, Rubin’s multiple imputation, and a Bayesian conditional probability model. The Bayesian conditional probability model uses the TUS data to develop a posterior distribution of the technology holdings and then integrates the leisure type model estimated on the NTS data over this posterior distribution. The results reiterate the fact that this is the most behavioural of the three data pooling techniques, and also support our hypothesis that household technology holdings are correlated with OH leisure activity patterns.
  Authors: Sivakumar, Aruna; Polak, John W.
  Authors: Sivakumar, Aruna; Polak, John W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-3846
• Wide-area Congestion Performance Monitoring Using Probe Data
  Abstract: This paper describes a web-based visual analytics monitoring system for identifying major bottlenecks, reporting on travel time reliability, and displaying other congestion measures using private sector vehicle probe data fused with agency incident and event data where available. This system represents an exponential leap forward in capabilities for state DOTs, MPOs, and researchers in their efforts to report on system performance in terms of speed and ease of access, usability, and overall data availability. This paper demonstrates how states are using the system to justify construction projects, demonstrate the benefits of completed transportation projects, identify areas for improvement, and analyze travel times using a variety of data sources with an emphasis on vehicle probe data. The underlying system includes probe data from as early as 2008 through today that is being used to analyze trends from year-to-year, month-to-month, and day-to-day. The resulting suite of tools provides significant new capabilities to researchers and analysts that will likely fuel additional research. A complete description of all functionality can be viewed at the following link which contains a webcast of the suite. http://vpp.ritis.org/suite/screencast
  Authors: Pack, Michael L.
  Authors: Pack, Michael L.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 627
  Paper Number: 13-3853
• Simplified Two-Stage Choice Set Formation Models Incorporating Observed Choice Set Data
  Abstract: The implementation of a theoretically sound, two-stage discrete-choice modelling paradigm incorporating probabilistic choice sets is impractical when the number of alternatives is large, which is a typical case in most spatial choice contexts. In the context of residential location choice, Kaplan, Bekhor and Shiftan (2009, 2011, 2012) (KBS) developed a semi-compensatory choice model incorporating data of individuals searching for dwellings observed using a customised real estate agency website. This secondary data is used to compute the probability of considering a choice set that takes the form of an ordered probit model. In this paper, we illustrate that the simplicity of the KBS model arises because of an unrealistic assumption that individuals’ choice sets only contain alternatives that derive from their observed combination of thresholds. Relaxing this assumption, we introduce a new probabilistic choice set formation model that allows the power set to include all potential choice sets derived from variations in thresholds’ combinations. In addition to extending the KBS model, our proposed model asymptotically approaches the classical Manski model, if a suitable structure is used to categorize alternatives. In order to illustrate the biases inherent in the original KBS approach, we compare it with our proposed model and the MNL model using a Monte Carlo experiment. The results of this experiment show that the KBS model causes biases in predicted market share if individuals are free to choose from any potential choice sets derived from combinations of thresholds.
  Authors: Zolfaghari, Alireza; Sivakumar, Aruna; Polak, John W.
  Authors: Zolfaghari, Alireza; Sivakumar, Aruna; Polak, John W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-3870
• Spatial Approach for Assessing Energy-Related Impacts on Transportation Systems
  Abstract: Like other states around the country, Texas has experienced a boom in energy-related activities in recent years, particularly in wind power generation and extraction of oil and natural gas. While energy developments contribute to the state’s energy reliability, they also result in many short-term and long-term impacts on the state’s transportation system. Recently, Texas conducted an evaluation of impacts of energy developments on the state right of way, including pavement impacts, roadside impacts, operational and safety impacts, and economic impacts. During the evaluation, the research team developed a spatial approach for energy impact assessment and prediction based on a set of spatial databases of existing energy- and transportation- related datasets. The energy datasets included non-renewable energy datasets, renewable energy datasets, energy use datasets, and geology-related datasets. The transportation datasets included oversize/overweight routing and enforcement datasets, traffic safety datasets, transportation infrastructure datasets, and transportation planning datasets. The development of the spatial databases involved significant efforts of data collection and processing. The developed spatial databases enabled a wide range of queries and reports that helped the research team to understand the distribution and magnitude of energy activities in relation to transportation facilities. In addition to information about data sources and data processing methodologies, the spatial databases provided state transportation officials a useful framework for energy-related transportation planning and assessment of energy impacts and their trends. The paper includes valuable lessons that can help other states to fully utilize spatial data sources for understanding energy-related impacts and developing mitigation strategies.
  Authors: Li, Yingfeng; Quiroga, Cesar; Kraus, Edgar
  Authors: Li, Yingfeng; Quiroga, Cesar; Kraus, Edgar
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Energy; Pavements
  Session: 534
  Paper Number: 13-3878
• Modeling Connection Between Activity-Travel Patterns and Subjective Well-being
  Abstract: Transportation forecasting models are invariably used to help inform policy and investment decisions. Although the logsum terms in choice model components have often been used to measure consumer surplus or welfare, such terms do not fully capture the welfare, satisfaction, and well-being that people derive from their activity-travel patterns. As a result, transportation models are currently unable to adequately reflect the impacts of policy and investment decisions on people’s well-being and overall quality of life. This paper presents a multivariate ordered response probit model that is able to capture the influence of activity-travel characteristics on subjective well-being while accounting for unobserved individual traits and attitudes that predispose people when it comes to their emotional feelings. The model, estimated on the well-being module of the 2010 American Time Use Survey data set, shows that activity-travel characteristics, besides individual and household demographics, are important determinants of feelings of well-being that people derive from their activity episodes. It is found that activity duration, activity start time, and child accompaniment significantly impact feelings of well-being for different activities. Differences were found in feelings of well-being depending on whether activities were pursued in-home or out-of-home. Error correlations were significant, suggesting that the multivariate ordered probit modeling approach is appropriate when analyzing measures of well-being across activity categories. By integrating the well-being model presented in this paper with activity-based microsimulation models of travel demand, measures of well-being for different demographic segments may be estimated and the impacts of alternative policy and investment decisions on quality of life can be better assessed.
  Authors: Archer, Melissa; Paleti, Rajesh; Konduri, Karthik Charan; Pendyala, Ram M.; Bhat, Chandra R.
  Authors: Archer, Melissa; Paleti, Rajesh; Konduri, Karthik Charan; Pendyala, Ram M.; Bhat, Chandra R.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-3883
• Dynamic Forecast of Incident Clearance Time Using Adaptive Artificial Neural Networks
  Abstract: This paper presents an adaptive model to forecast the clearance time of real-time traffic incidents. This information is vitally important for the incident management process, to adequate the operational response to the incident zone, and to predict network conditions induced by the incident. It is essential to design proactive measures in terms of traffic control and traveller information to mitigate impending congestion and safety impacts. This is a challenging problem in real-time environments because the incident characteristics reported by incident responders or others, which are needed to model and forecast in a timely way, are limited, often inaccurate and vague. Therefore, an adaptive model was developed to capture the incident characterization dynamics to improve the predictive performance. This solution includes four adaptive Artificial Neural Network-based models, which are activated with incoming data, from the incident notification until the point of the incident road clearance. The first model (M1) uses basic incident characteristics usually available with the incident notification, such as the type, location, time, road geometry and blockages. Then M2 uses response times and arrival demand and outputs from M1. Next, M3 uses the number and type of vehicles involved as well as the outputs from M2. At last, M4 uses incident severity together with M3 outputs.This model was calibrated and tested using incident records from Portuguese highways, and the performance shows that M4 was able to estimate 72% of incidents with less than 10 minutes error and about 92% with less than 20 minutes error. This model tends to overestimate in about 75% the prediction values for major accidents, minor incidents and road works and about 85% of incidents with duration up to 80 minutes are under estimated, which are opportunities for further improvements.
  Authors: Lopes, Jorge
  Authors: Lopes, Jorge
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-3885
• Evaluation of Alternative Technologies to Estimate Travel Time on Rural Interstates
  Abstract: New technologies are becoming more and more readily available to collect vehicular traffic data in a cost-effective and non-intrusive fashion. The primary objective of this paper is to present the results of an evaluation of alternative technologies to estimate travel time along a segment of Interstate 91 in Western Massachusetts where traffic volumes and corresponding sample sizes are expected to be relatively low. The first means of data collection uses global positions system technology (GPS) technology employed by INRIX, an enterprise that provides traffic-related information including travel time, directions, and other driver services. The second means uses Bluetooth technology and field data collected by another vendor, BlueTOAD, along the I-91 study site. A third means of data collection using a license plate based method was devised by the authors to provide “ground truth” travel time against which the results of the above two technologies were compared and evaluated. The data analysis showed that sufficient sample sizes were collected and that the accuracy of travel times estimated from data provided by both vendors (i.e., GPS-based INRIX and Bluetooth-based BlueTOAD) is acceptable since their mean absolute percentage errors (MAPE) were consistently less than 6 percent.
  Authors: Jia, Chaoqun; Li, Qiao; Oppong, Samuel; Ni, Daiheng; Collura, John; Shuldiner, Paul W.
  Authors: Jia, Chaoqun; Li, Qiao; Oppong, Samuel; Ni, Daiheng; Collura, John; Shuldiner, Paul W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 766
  Paper Number: 13-3892
• Monitoring Urban Bicycle Volumes Using Inductive Loops at Signalized Intersections
  Abstract: As a sustainable transport mode, cycling is getting more attention from policy makers and transport planners throughout the world. However, in the Netherlands, and elsewhere, system wide bicycle volume data are lacking. Municipalities in the Netherlands rely on national travel survey data, combined with visual counts. The lack of data on bicycle volumes hampers municipalities to plan and improve bicycle facilities. In the Netherlands, inductive loops for both vehicles and bicycles are present at signalized intersections. In this paper, we use data from these loops in the town of Enschede, to examine the actual bicycle volumes. We show that inductive loops can be used when we compare their counts with visual counts at a few signalized intersections. At low to medium bicycle volumes (up to 200 cyclists passing per hour), the detections by the inductive loops comply well with the actual number of cyclists. At higher volumes, the probability increases that two (or more) cyclists are detected as one. This happens because of the reduction of time headways, making two successive cyclists undistinguishable. By assuming a random arrival process within a certain arrival time window, we can explain the rate of underestimation at high volumes, and correct for this. The results of this study can be applied by practitioners to convert inductive loop data into bicycle volumes and will be a valuable source of data for road authorities in medium-sized cities in the Netherlands.
  Authors: Veenstra, Sander; Thomas, Tom; Geurs, Karst T.
  Authors: Veenstra, Sander; Thomas, Tom; Geurs, Karst T.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists
  Session: 425
  Paper Number: 13-3901
• Generalized Nonlinear Models for Rear-End Crash Risk Analysis
  Abstract: A Generalized Nonlinear Model (GNM)-based approach for modeling highway rear-end crash risk is formulated using Washington State traffic safety data. Previous studies majorly focused on causal factor identification and crash risk modeling using Generalized linear Models (GLMs), such as Poisson regression, Logistic regression, etc. However, their basic assumption of a generalized linear relationship between the dependent variable (for example, crash rate) and independent variables (for example, contribute factors to crashes) established via a link function can be often violated in reality. Consequently, the GLM-based modeling results could provide biased findings and conclusions. In this research, a GNM-based approach is developed to utilize a nonlinear regression function to better elaborate non-monotonic relationships between the independent and dependent variables using the rear end accident data collected from ten highway routes from 2002 through 2006. The results show for example that truck percentage and grade have a parabolic impact: they increase crash risks initially, but decrease them after the certain thresholds. Such non-monotonic relationships cannot be captured by regular GLMs which further demonstrate the flexibility of GNM-based approaches in the nonlinear relationship among data and providing more reasonable explanations. The superior GNM-based model interpretations help better understand the parabolic impacts of some specific contributing factors for selecting and evaluating rear-end crash safety improvement plans.
  Authors: Lao, Yunteng; Zhang, Guohui; Wang, Yinhai
  Authors: Lao, Yunteng; Zhang, Guohui; Wang, Yinhai
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3903
• Estimating Link Travel Time from Low-Frequency GPS Data
  Abstract: Existing methods of estimating travel time from GPS data are not capable of simultaneously taking into account the issues related to uncertainties associated with GPS and spatial road network data, low sampling frequency, vehicle coverage on the network, time window length and vehicle sample size. This paper reports the results of a research study that sought to better estimate travel time using vehicle trajectory data from moving sensors (i.e. probe vehicles equipped with GPS) in ‘near’ real-time.In the proposed methodology, accurate locations of vehicles on a link are first determined by map-matching (MM) so as to reduce the potential positioning errors associated with GPS and digital road map. Two mathematical methods are then developed to estimate link travel time from map-matched GPS fixes, vehicle speed and network connectivity information with a special focus on sampling frequency, vehicle sample size and time window length. GPS data from Interstate I-880 (California, USA) for a total of 73 vehicles over 6 hours were obtained from the UC-Berkeley’s Mobile Century Project. The original GPS dataset that was in 3 sec sampling frequency has been extracted at different sampling frequencies such as 6, 30, 60 and 120 seconds. This facilitates to evaluate the performance of a travel time estimation method at different sampling frequencies. The results are then validated against reference travel time data collected from high resolution video cameras. The results indicates that factors such as vehicle sample size, data sampling frequency, vehicle coverage on the links and time window length all influence the accuracy of link travel time estimation. The performance has found to be better in the 5 minutes time window length for 60 sec GPS sampling frequency.
  Authors: Sanaullah, Irum; Quddus, Mohammed A.; Enoch, Marcus Paul
  Authors: Sanaullah, Irum; Quddus, Mohammed A.; Enoch, Marcus Paul
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-3909
• Multimodal Public Transport Demand: Cointegration Time-Series Approach
  Abstract: In this paper we investigate demand in a multimodal public transportation context. Demand is expressed as a function of operational and macroeconomic factors and is analyzed using a time-series cointegration and error correction approache. This allows for treating non stationary data and for determining short term and long term elasticities and at the same time estimating the speed of convergence from the short to the long term effects. As expected, short run elasticities appear lower than the long run ones, possibly because in the short run changes in explanatory factors are smaller and because behavior is governed by resistance to change. Fare and Income appear to have the greatest impact on public transport demand and also the greatest difference between short and long run elasticities.
  Authors: Milioti, Christina; Karlaftis, Matthew G.
  Authors: Milioti, Christina; Karlaftis, Matthew G.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-3910
• Using Signature-Based Vehicle Reidentification to Measure Lane-Changing Maneuvers
  Abstract: This paper provides insight to lane change maneuver data by employing a real-time vehicle re-identification and classification system capable of producing individual vehicle matches and classes based on inductive signatures during congested and uncongested conditions. Vehicle re-identification results for a 0.66 mile multilane freeway segment are compared to manually matched vehicle pairs from video data. Examination of lane change probabilities show that re-identification is capable of reproducing lane change maneuvers with minimal error (root mean square error = 0.0162 and correlation coefficient= 0.927). Differences in lane change probability by level-of-service (LOS), vehicle class, and segment type are also examined. Results show that there is variability in lane change probability by LOS and vehicle class. Although other studies have quantified lane change behavior using vehicle re-identification, none has been successful in obtaining measures during congestion and for separate vehicle classes. Not only would the information gathered from this research be useful in calibrating microsimulation models but also could be used as the basis of real-time traffic calming strategies designed to reduce lane changing at the onset of congestion. In addition to an evaluation of merging behavior using re-identification, improvements to the current re-identification methodology based on lane changing to increase correct classification rates are proposed.
  Authors: Regue, Robert; Hernandez, Sarah Vavrik
  Authors: Regue, Robert; Hernandez, Sarah Vavrik
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-3911
• Collision Propensity Index for Unsignalized Intersections: Structural Equation Modeling Approach
  Abstract: The objective of this paper is to develop a quantitative collision propensity index (CPI) that captures the overall propensity of a given surrounding environment to cause accidents at un-signalized intersections. Using structural equation modeling, the index can be estimated from observed geometric, vehicular, driver-related, and traffic-related characteristics. Utilizing the California Department of Transportation's data repository, information on 4388 collisions occurring at 2709 different intersections was collected and processed. A statistically significant converging structural equation model was found reflecting the safety impact of different surrounding elements/dimensions on driving behavior: The CPI provides (a) a basis for quantifying the effects of the aforementioned characteristics on traffic safety and/or incident properties, (b) a basis for comparing the differences between the dimensions affecting collision propensity based on different exogenous measures’ classification schemes and (c) ranking the corresponding un-signalized intersections for improved safety performance. The framework and methodology used to develop this index has the potential to support safety policy analysis and decision making.
  Authors: Schorr, Justin; Hamdar, Samer Hani; Vassallo, Terasa
  Authors: Schorr, Justin; Hamdar, Samer Hani; Vassallo, Terasa
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-3915
• Robustness and Computational Efficency of Kalman Filter Estimator of Time-Dependent Origin-Destination Matrices Exploiting ICT Traffic Measurements
  Abstract: Origin-Destination (OD) trip matrices, which describe the patterns of traffic behavior across the network, are the primary data input used in principal traffic models and therefore, a critical requirement in all advanced systems that are supported by Dynamic Traffic Assignment models. However, because OD matrices are not directly observable, the current practice consists of adjusting an initial or seed matrix from link flow counts which are provided by an existing layout of traffic counting stations. The availability of new traffic measurements provided by ICT applications allows more efficient algorithms, namely for the real-time estimation of OD matrices based on modified Kalman Filtering approaches exploiting the new data. The quality of the estimations depends on various factors, like the penetration of the ICT devices, the detection layout and the quality of the initial information. Concerning the feasibility of real-time applications, another key aspect is the computational performance of the proposed algorithms for urban networks of sensitive size. This paper presents the results of a set of computational experiments with a microscopic simulation of a network of the business district of Barcelona, which explore the sensitivity of the Kalman Filter estimates with respect to the values of the design factors, and its computational performance.
  Authors: Barceló, Jaume; Montero, Lidia; Bullejos, Manuel; Linares, Mari Paz; Serch, Oriol
  Authors: Barceló, Jaume; Montero, Lidia; Bullejos, Manuel; Linares, Mari Paz; Serch, Oriol
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 486
  Paper Number: 13-3919
• Analysis of the Effects of Activities While Traveling on Travelers' Sentiment
  Abstract: Travel involves various onboard activities. The emergence of ICT (Information and Communication Technologies) has increased such activities and added new dimensions to them. This study intends to analyze the effects of various onboard activities including the use of ICT on trip-makers’ sentiments during trips. This study employs the Daily Reconstruction Method to examine whether or not the feelings that trip-makers have are positive or negative. Also, the Seemingly Unrelated Probit Regression and Univariate Probit models are used to analyze the relationship between onboard feelings and onboard activities by travel mode. This study finds that onboard activities using ICT devices are valued among trip-makers and tend to have positive effects on their onboard feelings. However, this study also finds that the effects are not homogenous. The findings indicate that emerging ICT related onboard activities can be instrumental in improving people’s travel experience and in converting choice automobile users to choice transit riders.
  Authors: Rhee, Kyoung-ah; Kim, Joon-Ki; Lee, Backjin; Kim, Sungyop; Lee, Young-Ihn
  Authors: Rhee, Kyoung-ah; Kim, Joon-Ki; Lee, Backjin; Kim, Sungyop; Lee, Young-Ihn
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 815
  Paper Number: 13-3922
• Estimation of Changes in Rail Ridership Through Onboard Survey: Did Free Wi-Fi Make a Difference to Amtrak's Capitol Corridor Service?
  Abstract: Amtrak launched free Wi-Fi service on the California Capital Corridor (CC) on November 28, 2011. To study the impact of free Wi-Fi on ridership, an on-board survey was conducted in March, 2012. Through the descriptive analysis, several conventional factors (trip frequency in 2011, trip purpose, station to station distance and employment) as well as Wi-Fi are found to have some impact on the expected trip frequency in 2012. A linear regression model based on the specification of three market segments was built to better understand the impact of selected variables on the expected number of CC trips in 2012. According to the model results, past trip frequency is the most important predictor of future frequency. The impact of free Wi-Fi on 2012 trip frequency is statistically significant and positive for the two (lower-frequency and higher-frequency) continuing rider segments, albeit modest in magnitude. Using the estimated parameters from the model, the number of trips the sample expects to make in 2012 is 1.3% higher than would have been the case without free Wi-Fi. Furthermore, the effect clearly differs among the three segments: lower-frequency continuing riders (those using CC less than once a week in 2011) expect to make 8.5% more trips than if Wi-Fi were not available, whereas the corresponding number for higher-frequency continuing riders (using CC once a week or more in 2011) is 0.7%. Wi-Fi has no statistically significant impact on the expected 2012 trip frequency for new riders.
  Authors: Dong, Zhi; Mokhtarian, Patricia L.; Circella, Giovanni
  Authors: Dong, Zhi; Mokhtarian, Patricia L.; Circella, Giovanni
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 815
  Paper Number: 13-3946
• Analysis of Aggregate Crash Data in the United States for 1967-2010
  Abstract: In a previous paper the authors completed a country-level as well as a time-dependent road safety analysis focusing on countries where data were available for a longer period of time (1965-2009). One of the conclusions was that the USA is lagging behind compared to twenty five – mostly European – countries in terms of fatalities per population. In some European countries this value is already below 5 fatalities per 100,000 population, whereas in the USA it was around 11 in 2010. A possible explanation for that was higher vehicle miles traveled and preference for car travel.This paper – as a continuation of the previous research –addresses two issues. One is a thorough international comparison of road safety indicators in the US and some selected countries. The second is to investigate the road safety situation and trends on the state level.The evolution of road safety in the USA on the national as well as the state-level is modeled for a longer period of time (1967-2010). Fatality rates (fatalities per population and VMT) are used for the comparison of countries as well as US states and the change of these values over time is analyzed. The states with rates lower than the national average are generally more urban or smaller in area, and those with rates higher than the national average are generally more rural or larger in area. The fatality rates in the former group are comparable to those for the best countries in Western Europe.
  Authors: Borsos, Attila; Koren, Csaba; Ivan, John N.; Ravishanker, Nalini
  Authors: Borsos, Attila; Koren, Csaba; Ivan, John N.; Ravishanker, Nalini
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3947
• Development of a Geographic Information System for SafetyAnalyst for Location Selection and Output Visualization
  Abstract: SafetyAnalyst was developed as a cooperative effort by the Federal Highway Administration (FHWA) and participating state and local agencies. Released in 2010, the system is a set of software tools developed to aid state and local highway agencies in highway safety management. SafetyAnalyst uses the empirical Bayes method and incorporates all the steps of the roadway safety management process. However, it lacks the Geographic Information System (GIS) component; SafetyAnalyst provides only the data interface needed to exchange spatial data. Given the spatial nature of crash analysis, there is a need for a GIS component to allow users to graphically select locations and display analysis results from SafetyAnalyst. SafetyAnalyst assumes that an agency will adapt its existing GIS system to provide that capability. However, it is unlikely that an agency will have an existing GIS system that can be customized to work with the unique file structures of SafetyAnalyst. This paper discusses SafetyAnalyst, its input and output file structures, and a standalone GIS system designed to interface with SafetyAnalyst. The system provides an alternate method for selecting locations for analysis by SafetyAnalyst using a graphical display. The system also provides a graphical display of the results from SafetyAnalyst’s network screening module. While the system was developed for Florida, it can be easily customized for similar applications in other states.
  Authors: Ma, Meng; Alluri, Priyanka; Gan, Albert
  Authors: Ma, Meng; Alluri, Priyanka; Gan, Albert
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3969
• Real-Time Traffic Network State Estimation and Prediction with Decision Support Capabilities: Application to Integrated Corridor Management
  Abstract: This paper presents a real-time traffic network state estimation and prediction system with built-in decision support capabilities for traffic network management. The system seeks to provide traffic network managers with the capabilities to estimate the current network conditions, predict congestion dynamics, and generate efficient traffic management schemes for recurrent and non-recurrent congestion situations. The system adopts a closed-loop rolling horizon framework in which network state estimation and prediction modules are integrated. The system is applied in the context of Integrated Corridor Management (ICM), which is envisioned to provide a system-based approach for managing congested urban corridors. A genetic algorithm methodology is developed to generate efficient traffic management schemes that integrate preapproved control actions by all managing agencies. The system is applied to a section of a commuter corridor in Dallas, Texas. The results show the ability of the system to improve the overall network performance during hypothetical incident scenarios.
  Authors: Hashemi, Hossein; Abdelghany, Khaled F.; Hassan, Ahmed; Lezar, Maverick
  Authors: Hashemi, Hossein; Abdelghany, Khaled F.; Hassan, Ahmed; Lezar, Maverick
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-4029
• Bayesian Analysis of Personal Daily Activity Patterns
  Abstract: In this article, we consider data for residents of Orange and San Diego counties in California to study travel behavior in five activity categories – work, maintenance, recreational and social, personal, and pick-up or drop-off. We build and estimate a joint discrete choice model for the five categories that captures the inter-dependence among activities and accounts for possible correlations between number of participations in different activities. Because the likelihood function for the model is analytically intractable, we discuss estimation methods that circumvent the likelihood intractability by employing Markov chain Monte Carlo (MCMC) simulation and data augmentation. The methodology is computationally efficient, simple to implement in practice, and permits straightforward evaluation of covariate effects and comparison of competing models. We consider several alternative model specifications, compare them by their marginal likelihoods and posterior odds ratios and evaluate the covariate effects of key variables such as change in household structure, size, income level, or employment status, to determine their impact on the probability and extent of participation in different activity types. Our findings confirm the importance of household structure for activity pattern and allow us to isolate interesting differences in the behavior of household members. These results help further our understanding of household travel behavior and provide a foundation that can be used in forecasting and quantifying various policy effects.
  Authors: Allahviranloo, Mahdieh; Jeliazkov, Ivan
  Authors: Allahviranloo, Mahdieh; Jeliazkov, Ivan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4038
• Adjustment Factors for Estimating Miles Traveled by Nonmotorized Traffic
  Abstract: Traffic counts are an important piece of information used by transportation planners; however, while count programs are common for motor vehicles most efforts at counting non-motorized traffic – cyclists and pedestrians – are minimal. Long-term, continuous counts of non-motorized traffic can be used to estimate month of year and day of week adjustment factors that can be used to scale short-duration counts to estimates of annual average daily traffic. Here we present results from continuous counts of non-motorized traffic at 6 locations on off-street trails in Minneapolis, MN using two types of automated counters (active infrared and inductive loop detectors). We found that traffic volumes varied significantly by location, but the month of year and day of week patterns were mostly consistent across locations and mode (i.e., cycling, walking, or mixed mode). We give examples of how this information could be used to extrapolate short-duration counts to estimates of annual average daily traffic as well as Bicycle Miles Traveled (BMT) and Pedestrian Miles Traveled (PMT) for defined lengths of off-street trails. More research is needed to determine if non-motorized traffic patterns (and subsequently our adjustment factors) for off-street trails are comparable to those for on-street non-motorized travel or for other geographic areas.
  Authors: Lindsey, Greg; Chen, Junzhou; Hankey, Steve
  Authors: Lindsey, Greg; Chen, Junzhou; Hankey, Steve
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists
  Session: 425
  Paper Number: 13-4082
• Obtaining Public Transport Level-of-Service Measures with In-vehicle GPS Data and Freely Available GIS Web-Based Tools
  Abstract: Information technology has set new standards within public transport system management strategies, and renewed attention has been paid to vehicle level-of-service (LOS) performance measurement techniques in recent years. Specifically, in-vehicle GPS technology provides a good opportunity to collect substantial amounts of useful data for accurate public transport LOS measuring. Handling these rich data can be labour intensive, time consuming and challenging, especially in highly dense networks. Systematic, easy to apply, and inexpensive techniques to process information quickly and display LOS outcomes efficiently are required.The main aim of this paper is to present a procedure to obtain LOS measures at any spatial and temporal aggregation level in the case of dense bus networks using freely available map and geographic software. The proposed methodology is highly flexible as it can accommodate either fixed or variable space-time aggregations; it can handle vast amounts of GPS data yielding LOS results relatively quickly. Furthermore, it can be implemented at relatively low cost in terms of software requirements, using freely available software.An illustration of the proposed procedure and its results to obtain LOS measures among bus stops is reported, using the geographic location of bus stops and offline GPS data available (every 30 seconds) for all operating buses in Santiago´s public transport system.
  Authors: Arellana, Julian; Ortuzar, Juan de Dios; Rizzi, Luis I.; Zuñiga, Felipe
  Authors: Arellana, Julian; Ortuzar, Juan de Dios; Rizzi, Luis I.; Zuñiga, Felipe
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 299
  Paper Number: 13-3896
• Social Dimensions of Walking: Understanding How Social Environment Influences Walking Trips
  Abstract: Walking is an important part of a healthy and active lifestyle, but in Canada and many other countries in the world there is a lack of walking. This lack of walking can lead to health problems and increased costs to taxpayers. Past research has examined how walking is influenced by the individual and physical environments, but few have focused on the social environment. The social environment is made up of companionship, encouragement, role models, and neighborhood social cohesion. This study examines how each component of the social environment influences walking while controlling for the individual and physical environments in Hamilton, Canada using a linear regression model. The results find walking alone (companionship) increases walking, having doctor requesting that they walk decreases walking, living in a close-knit neighborhood increases walking, and living in a neighborhood where people do not share the same value decreases walking.
  Authors: Clark, Andrew F.; Scott, Darren M.
  Authors: Clark, Andrew F.; Scott, Darren M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting
  Session: 735
  Paper Number: 13-4223
• Some Insights into Roadway Geometric Effects on Interstate Crash Occurrence from a Crash Typology Perspective
  Abstract: This paper proposes a crash frequency modeling typology for interstate freeways. Using a nine-year continuous panel of crash histories of total crash frequencies on interstates in Washington State for the period (1999-2007), random parameter negative binomial (RPNB) models are estimated for a variety of crash related outcomes. A total of 21 different outcomes were assessed in terms of four typologies: a) severity, b) number of vehicles involved, c) crash type, and d) crashes by interchange type. The sub-models within these major categories included: RPNB specifications for all severities (property damage only, possible injury only, evident injury, disabling injury and fatality), number of vehicles involved (one-vehicle to five-or-more-vehicle), crash type (sideswipe, same direction, overturn, head-on, fixed object, rear-end and other), and location types (urban interchange, rural interchange, urban non-interchange, rural non-interchange). A total of 1,153 directional segments comprising of the seven Washington State interstates were analyzed, yielding a statistical model of crash frequency based on 10,377 observations. It was found that several geometric effects were random in their interaction with the logarithm of average daily traffic, meaning the interaction varied from segment to segment. These results suggest that segment specific insights into crash frequency occurrence can be improved for appropriate design policy and prioritization insights via more accurate characterization with interactions. This suggests that flow interactions are critical even after flow is accounted for as a main effect. The conventional approach has been to include flow as a main effect either in logarithmic form or in linear form.
  Authors: Venkataraman, Narayan S; Ulfarsson, Gudmundur Freyr; Shankar, Venky N.
  Authors: Venkataraman, Narayan S; Ulfarsson, Gudmundur Freyr; Shankar, Venky N.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4344
• Experimental Design of Personalized Travel Plan to Encourage Behavioral Change
  Abstract: This paper describes the experimental design of a voluntary travel behavior change program implemented in Cagliari, Italy. The objective of the work is to contribute to understand the fundamentals of travel behavioral process by identifying the factors underlying behavioral change. More specifically, the PTP program proposed in this work involved 109 participants, from February 2011 to June 2012, in two steps: a first one-week activity-travel data collection to observe current behaviors and a second one-week activity-travel data collection to monitor behavior, after the provision of personalized travel plans. The program has been evaluated observing the behavioral change during the second week of the program (monitoring week) and three months after the end of the program. Further, the factors underlying behavioral change have been analyzed comparing the quantitative feedback provided to participants showing a behavioral change vs. participants who did not change. Results seem to have important policy implications. Indeed, they indicate that providing car users with detailed feedback about current behavior and existing alternatives have a general positive effect on behavioral change.
  Authors: Meloni, Italo; Sanjust, Benedetta; Spissu, Erika; Porcu, Silvio
  Authors: Meloni, Italo; Sanjust, Benedetta; Spissu, Erika; Porcu, Silvio
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4371
• Travel Time Distributions on Urban Streets: Estimation with Hierarchical Bayesian Mixture Model and Application to Traffic Analysis with High-Resolution Bus Probe Data
  Abstract: This paper develops a hierarchical Bayesian mixture travel time model to capture the interrupted nature of urban traffic flows. It uses high-resolution bus probe data to estimate travel times on urban streets for short links rather than for long paths, and reveals predominantly bimodal travel time distributions at the link level, with one mode corresponding to travels without delays and the other travels with delays. This bimodal travel time distribution is then used to analyze traffic operations and identify congestion. The advantage of the mixture model is demonstrated using empirical bus probe data, and the results are encouraging.
  Authors: Ji, Yuxiong; Zhang, H. Michael
  Authors: Ji, Yuxiong; Zhang, H. Michael
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-4377
• Data-Driven Particle Filter for Travel Time Prediction
  Abstract: The research presented in this paper develops a data-driven particle filter to predict travel times by sampling from historical data. In the proposed method, each particle corresponds to a travel time sequence from a database of historical data. The particle weight is calculated using a dissimilarity measure between measurement and particle sequences. A resampling method is developed in the data-driven particle filter to eliminate particles with low weights and re-select samples according to the probability of each track. Travel time predictions are computed by aggregating the weighted travel times of each particle. A freeway stretch from Newport News to Virginia Beach is selected to test the proposed algorithm using five-minute aggregated traffic data in 2010 provided by INRIX. The travel time prediction results during the summer season demonstrate that the proposed method outperforms two Kalman filter methods by reducing the prediction error by 30% and 57%.
  Authors: Chen, Hao; Rakha, Hesham
  Authors: Chen, Hao; Rakha, Hesham
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-4392
• Bayesian Approach to Real-Time Traffic State Estimation Using Particle Probability Hypothesis Density with Appropriate Clutter Intensity
  Abstract: Prediction of traffic flow variables such as traffic volume, travel speed or travel time for a short time horizon is of paramount importance in traffic control. Hence, data assimilation process in traffic modeling for estimation and prediction plays a key role. However, the increasing complexity, non-linearity and presence of various uncertainties (both in the measured data and models) are important factors affecting the traffic state prediction. To overcome this problem, new methodologies have to be investigated. In this aim, we propose in this paper the use of Probability Hypothesis Density (PHD). This methodology is intensively studied, developed and improved for the purposes of multiple object tracking and consists in the recursive state estimation of several targets by using the information coming from an observation process. However, some issues need to be studied, especially the clutter (false alarm) intensity. The goal of this paper is to expose the potential of the PHD filters for real-time traffic state estimation and the choice of an appropriate clutter intensity. This investigation is based on a Cell Transmission Model (CTM) coupled with the PHD filter. It brings a novel tool to the state estimation problem and allows one to estimate the densities in traffic networks. In this work, we compare this PHD filter with the particle filter (PF) which has been successfully applied in traffic control and conclude that the PHD filter can be seen as a relevant alternative that opens new research avenues.
  Authors: Canaud, Matthieu; Lyudmila, Mihaylova; El Faouzi, Nour-Eddin; Billot, Romain; Sau, Jacques
  Authors: Canaud, Matthieu; Lyudmila, Mihaylova; El Faouzi, Nour-Eddin; Billot, Romain; Sau, Jacques
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-4401
• Decision-Making Process and Factors Affecting Truck Routing
  Abstract: This research attempts to better understand truck routing behavior in terms of the decision-making process and the factors that affect routing choices. In order to collect data on the decision-making process, a computerized survey was employed to collect exploratory background information and Stated Preferences (SP). 252 road-intercept interviews of truck drivers have been conducted at three major corridors in North America, with 1121 valid SP observations. Both market segmentation and explicit modeling techniques have been used to analyze the data. Segmentations based on carrier/driver characteristics and shipment/route attributes are used to study the identity of routing decision makers and sources of information used in pre-trip planning and en-route adjusting. A random effects logit model was estimated using the SP data. The results show that (a) the trucking industry is highly heterogeneous with many entities contributing to the decision-making process, namely, carrier characteristics, driver characteristics, shipment attributes, and route attributes; (b) drivers do not always perceive delays negatively, there are cases when delays bring about benefits and therefore are preferred by certain groups of drivers; (c) truck drivers tend to prefer a toll road if the toll cost is covered by their employer.
  Authors: Sun, Yichen; Toledo, Tomer; Rosa, Katherine; Ben-Akiva, Moshe E.; Flanagan, Kate; Sanchez, Ricardo; Spissu, Erika
  Authors: Sun, Yichen; Toledo, Tomer; Rosa, Katherine; Ben-Akiva, Moshe E.; Flanagan, Kate; Sanchez, Ricardo; Spissu, Erika
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Freight Transportation
  Session: 410
  Paper Number: 13-4404
• Large-Scale Agent-Based Transport Simulation in Shanghai, China
  Abstract: The activity-based model system is being coined as the next-generation demand forecasting model. The agent-based transport simulation toolkit MATSim is a fully integrated system that models decisions from the long-term to the short-term, and these decisions in Matsim are activity-based models. By applying MATSim to the large scenario of Shanghai, a large scale multi agent-based transport simulation in Shanghai is presented in this paper. The algorithms of integrating new data in Shanghai with Matsim inputs such as synthetic population, facilities and network are separately designed according to data characteristics. Then, the activity-based modelling is introduced to generate population plans, and activity preplanning are employed to learn the better travel plans, while scoring for a plan is modelled by using utility-based approach. Finally, a full MATSim-based simulation platform for Shanghai scenario is built in detail. The scenario contains 200 thousand synthetic persons and they are simulated on a network with 50 thousand links. The relaxed state of simulation system is reached after 100 iterations of the replanning procedures, and the mode choice, route choice and activity time allocation modules are used to optimized the activity plans of agents. The feasibility of transport simulation in Shanghai by MATSim is validated against the mode split and the observed counts. Extensive simulation results on the designed Shanghai simulation scenarios indicates that most of the observed counts are matched quite well with the traffic simulation volumes, and the potential of MATSim for large-scale dynamic transport simulation has been demonstrated.
  Authors: Zhang, Lun; Yang, Wenchen; Wang, Jiamei; Rao, Qian
  Authors: Zhang, Lun; Yang, Wenchen; Wang, Jiamei; Rao, Qian
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-4405
• Assist-me: Postprocessing Tool for Transportation Planning Model Output
  Abstract: In this paper, we present ASSIST-ME (Advanced Software for State-wide Integrated Sustainable Transportation System Monitoring and Evaluation), a software application developed on a customized version of the ArcGIS 9.2 Developer Engine in Microsoft .NET Framework, as a tool to visualize and analyze the output of transportation planning models in a geographic information system (GIS) environment. The tool is built on a flexible framework that allows for adoption of any traditional transportation planning model, as demonstrated in this paper using the output of two major transportation planning models from different software platforms used by separate agencies: •New York Metropolitan Transportation Council’s (NYMTC) New York Best Practice Model (NYBPM) – running in TransCAD•North Jersey Transportation Planning Authority’s (NJTPA) North Jersey Regional Transportation Model – Enhanced (NJRTM-E) – running in CUBE.ASSIST-ME was conceived as a tool to allow agencies and planners to easily work with transportation planning model output, analysis of which is often time-consuming and requires extensive training. It offers four key functionalities: Data Visualization, Demand Analysis, Path Analysis, and Benefit / Cost Analysis. While data visualization and demand analysis enable the user to easily work with direct model output, custom path and cost analysis tools were developed to conduct analyses beyond what other software packages and tools allow. In particular, the benefit/cost analysis functions utilize the latest quantification/monetization approaches employed in research and by government agencies, without the need to run external applications or procedures (such as emission functions generated from EPA’s MOVES). This process can be used for any planning scenario, but ASSIST-ME also allows for customization to alter/modify the input data or analysis procedures as per the user’s needs. The most important aspect of ASSIST-ME is that it incorporates data visualization, data analysis, and output reporting functionalities in a single user-friendly setting, which requires minimal training or knowledge of the models themselves.
  Authors: Ozbay, Kaan; Bartin, Bekir; Iyer, Shrisan; Mudigonda, Sandeep
  Authors: Ozbay, Kaan; Bartin, Bekir; Iyer, Shrisan; Mudigonda, Sandeep
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 793
  Paper Number: 13-4411
• Safety Benefits of Stability Control Systems for Motorcoach Buses
  Abstract: This paper contains an analysis of the potential safety benefits of electronic stability control systems (ESC) for motorcoach buses operating within the U.S.. Motorcoaches are defined here as flat-front, high platform buses equipped for intercity or long distance travel. The deployment of the stability technologies for single motorcoach buses is in its infancy. National crash databases do not include information that can be used to identify buses equipped with ESC; moreover, even if they could be identified, in the current stage of deployment it is unlikely that there would be sufficient data to evaluate the safety performance of the technology particularly given the low number of motorcoach crashes. In light of these limitations, this study examined all recent fatal motorcoach crashes utilizing information from the accident reports, formal studies such as NTSB, and information contained in reconstruction reports to determine the likelihood that the crash may have been prevented or mitigated should the motorcoach have been fitted with functioning ESC technology. From this analysis it was determined that assuming ESC was fitted to all motorcoach buses, savings from LOC and rollover crashes prevented are estimated at $25 million annually. While the financial benefits for motorcoaches were found to be limited because LOC crash events are rare, the intrinsic value of this technology will likely exceed the financial benefits, given that motorcoaches transport the public and there is an expectation that effective safety technology should be used even if the exposure is low. In particular, the risk of passenger casualties in a higher speed motorcoach crash is much greater than for other vehicles because of the large number of people on board.
  Authors: Woodrooffe, John
  Authors: Woodrooffe, John
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Motor Carriers; Safety and Human Factors
  Session: 777
  Paper Number: 13-4367
• Portable Roadside Sensors for Vehicle Counting and Speed Measurement
  Abstract: This paper focuses on the development of a portable roadside sensor system for measurement of traffic flow rate, vehicle speeds and vehicle classification. The sensor system consists of wireless anisotropic magnetic devices which do not require to be embedded in the roadway – The devices are placed next to the roadway and measure traffic in the immediately adjacent lane. The vehicle detection algorithm is based on thresholds and speed measurement is based on calculation of cross-correlation between longitudinally spaced sensors. Fast computation of cross-correlation is enabled by using frequency domain signal processing techniques. The calculation of vehicle length follows from using a combination of vehicle speed and vehicle occupancy measurements. Rejection of data from vehicles in non-adjacent lanes is done by using model based position analysis of the magnetic field of vehicles. Data is presented from a large number of vehicles on a regular busy urban road in the Twin Cities in Minnesota. Separately, a high accuracy differential GPS system is used to measure vehicle reference speeds to evaluate the accuracy of the speed measurement from the new sensor system. The speed measurement accuracy is shown to be of the order of 2%. The accuracy in vehicle detection using all of the collected urban road data is 100%.
  Authors: Taghvaeeyan, Saber; Rajamani, Rajesh
  Authors: Taghvaeeyan, Saber; Rajamani, Rajesh
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-4430
• Safety Evaluation of Horizontal Curves on Rural Undivided Roads
  Abstract: The objective of this research was to develop total crash and fatal/injury crash prediction models for rural horizontal curves on undivided roads, with focus on three distinct aspects. The first was an emphasis on assembling a high quality large dataset. Crash prediction models were developed using a dataset of 11,427 rural horizontal curves on Wisconsin State Trunk Network roads with over 13 different parameters and four distinct types of crash dataset. The second focus area was to use regression tree analysis in creating a simple model of horizontal curve safety aimed at practitioners of systemic road safety management and creating subsets of data which warranted further analysis. Regression tree results identified curve radius of approximately 2,500 feet as a significant point below which there is a marked increase in crashes on horizontal curves.The third focus area of this research was to compare horizontal curve crash prediction models using different crash datasets. Models based on crash dataset with and without crashes in the proximity of intersections were compared. The results show that when crashes on horizontal curves are selected where crash report forms indicate the presence of a horizontal curve, crashes in proximity of intersections do not impact model results significantly; therefore, the inclusion of such crashes would increase the size of dataset benefiting model development.
  Authors: Khan, Ghazan; Bill, Andrea R.; Chitturi, Madhav V.; Noyce, David A.
  Authors: Khan, Ghazan; Bill, Andrea R.; Chitturi, Madhav V.; Noyce, David A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4435
• Data Cleaning in Activity and Travel Surveys: Methodology Applied to Walk Trips
  Abstract: Activity-based household travel surveys are becoming much more common as states and metropolitan regions contemplate advancing their travel behavior forecasting abilities. Such activity and travel surveys are valuable for the estimation and calibration of activity-based travel demand forecasting models. Before travel survey records can be used, they must be edited using data cleaning processes that identify, reject, and/or correct internal inconsistencies, miscoded information, and other errors. Literature on travel survey data cleaning is sparse, and few travel survey data cleaning standards exist beyond ad-hoc rules of thumb. This paper presents a possible methodology for improving on data cleaning rules of thumb by borrowing statistical methods, especially from the field of robust statistics. The methodology was applied to the walk trip records of a household activity and travel survey conducted during 2011 in the Portland, Oregon, region. First, indicator variables were constructed to flag suspect walk trips. Next, visual inspection of the highest-ranking 5% of suspect walk trips was performed. The methodology identified 29 walk trips with an incorrect mode, 19 location errors, 39 trips with travel time errors, and 6 walk trips with inaccurate trip purposes. After correcting the mode errors and removing the trips with location errors, key walk calibration statistics were more reasonable, demonstrating the usefulness of a statistically-derived data cleaning methodology. Finally, the paper concludes with recommended foci for data cleaning efforts of activity-based household travel surveys.
  Authors: Singleton, Patrick A.
  Authors: Singleton, Patrick A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-4443
• Influence of Social Contacts and Communication Use on Travel Behavior: Smart-Phone-Based Study
  Abstract: In this paper we investigate the use of a smartphone database to explore influences on travel behavior. Our aim is to exploit the rich individual-level data available from the smartphone to study the influence of communication and social contacts (collected via phone call and sms logs) on spatial movement (collected via GPS). An advantage of smartphone data is the ability to collect such rich data without user input over a long period of time, and the disadvantage is the difficulty associated with processing the data. We work with three months of data from 111 people collected via a snowball sample. In studying travel behavior, we focus on high level measures of mobility as represented by the size of one’s activity space and one’s travel intensity (our dependent variables). We use as explanatory variables sociodemographics, spatial relationship between home and work, communication use (number of phone calls and sms), and the travel behavior of those in the sample who are connected to the respondent (where connectivity is measured by phone and sms contact). We describe how these variables were processed from the smartphone data and present estimation results from the regression analysis. We find that people tend to travel in a similar manner as those they are socially connected to (consistent with the social network and travel literature) and that communication use is a compliment to physical travel (consistent with the telecommunication and travel literature). The results, although preliminary, illustrate how smartphone data can be exploited to reveal complex features of travel behavior.
  Authors: Ythier, Jeanne; Walker, Joan L.; Bierlaire, Michel
  Authors: Ythier, Jeanne; Walker, Joan L.; Bierlaire, Michel
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 791
  Paper Number: 13-4464
• Sensor Performance in Measuring Vehicle Length
  Abstract: While most vehicle classification currently conducted in the United States is axle-based, some applications could be supplemented or replaced by length-based data. Common length-based methods are more widespread and can be less expensive, including loop detectors and several types of non-loop sensors (both sidefire and in-road sensors). The most frequently deployed data collection method is loop detectors, and most dual-loop installations have the capability of reporting vehicle lengths.This paper explores field and laboratory tests of loop detectors and non-loop sensors for their performance in determining vehicle length and vehicle speed. Field testing was conducted at four different locations in Minnesota and South Dakota. Ten different commercially available sensors were evaluated.The testing results indicated that across a variety of detection technologies, the loop detectors and non-loop sensors generally reported comparable length and speed data. The research also examined different loop configurations, and found that 6-foot x 6-foot loops performed similarly to 6-foot x 8-foot loops, while 6-foot x 6-foot quadrupole loops performed poorly for vehicles with high beds due to their relatively small magnetic field. Loop detector performance was found to not degrade with the variety of lead-in wire lengths that were tested. Laboratory testing conducted with a loop simulator confirmed the field testing and found that loop detector data is generally repeatable.This paper draws from findings of the Loop and Length Based Vehicle Classification pooled fund project [TPF-5(192)] led by the Minnesota Department of Transportation.
  Authors: Minge, Erik; Petersen, Scott
  Authors: Minge, Erik; Petersen, Scott
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-4469
• Even Perfect Regressions May Not Tell the Effect of Interventions
  Abstract: Suppose that there was a ‘well specified’ regression model, one in which the correct predictor variables were combined into the correct function, and that the unknown parameters were estimated using good and plentiful data. Can such a model be used to predict what change in the response variable is caused by a change in one of the predictor variables? Surprisingly the answer is: “No.” In this paper I identify the condition that often frustrates the causal interpretation of well specified regressions. I show how this very condition led astray several authors who used regressions to estimate the role of speed in accident generation
  Authors: Hauer, Ezra
  Authors: Hauer, Ezra
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-4477
• A Needs-Based Stated-Response Method to Predict Impacts of New Forms of Travel
  Abstract: This paper discusses a method to assess how people adjust their activity/travel patterns in response to changes in mobility options. Needs-based methods are employed in which multiple activity and travel episodes undertaken in service of a broader personal objective are analyzed as a pattern of linked behavior. The empirical study investigated how people would adjust their grocery shopping patterns if offered a one-way-usage carsharing service. A stated-choice/stated-adaptation survey instrument is proposed.Substantive findings relating to the impacts of one-way carsharing are discussed, as are the broader implications of viewing personal mobility behavior in this way.
  Authors: Le Vine, Scott; Adamou, Orestes; Polak, John W.
  Authors: Le Vine, Scott; Adamou, Orestes; Polak, John W.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4461
• Benefit-Cost Analysis of Investing in Data Systems and Processes for Data-Driven Safety Programs
  Abstract: Deciding to invest in data is often a challenge for transportation agencies. State transportation agencies often face budget constraints and pressure to use their limited resources on more tangible projects than data and information collection. Data investments often compete for funding with safety improvements to the infrastructure and roadway projects. Infrastructure improvements are visible to the driving public and often have immediate safety impacts; the impact of data investments may not be as obvious to the public. Investments in safety data, however, inform States’ decision-making process regarding which safety improvements can have the most impact and where those improvements can be most effective. The Federal Highways (FHWA) Office of Safety commissioned this research to develop guidance on the methodologies that can be applied to determine the benefits of investing in data, data systems, and processes for achieving a data-driven safety program. The components of this research included a Safety Data Investment Benefit-Cost Analysis Methodology, which established a methodology to quantify the potential impacts of investment in safety data improvement, a Decision-making Guidebook, which provided a step-by-step approach for representatives of State transportation agencies to follow and customize the methodology based on their level of existing data, and a Final Report, which detailed each phase of the research process and included the results of a comprehensive literature review on the economic costs and benefits of investing in roadway safety data.
  Authors: Lawrence, Michael Fitzpatrick; Cartwright-Smith, Devon; Lefler, Nancy X.; Mans, Janine; Nguyen, Paul
  Authors: Lawrence, Michael Fitzpatrick; Cartwright-Smith, Devon; Lefler, Nancy X.; Mans, Janine; Nguyen, Paul
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 614
  Paper Number: 13-4486
• Statistical Analysis of Mobility Impact of Urban Work Zones with Geocoded Lane Closure and Archived Loop Detector Data
  Abstract: Lane closures as a result of freeway work zone constitute 10% of urban congestion and relate to more than 87,000 annual crashes in the US. Researchers have been studying the mobility characteristics of work zones for many years, focusing on speed reduction, queue length, and capacity based on traffic flow data manually processed or collected for a limited number of work zones. With the increased availability of ITS data, especially geo-coded ITS data, new opportunities emerge for studying and evaluating the mobility impact of work zones. In this study, taking advantages of the comprehensive statewide ITS data archived at Traffic Operations and Safety (TOPS) lab, we correlate the detailed work zone data available through the WisLCS system to the 5-min loop detector data archives using the Wisconsin linear reference system STN(State Truck Network)-Link. Two statistical methods, one-sample percentile value test and two-sample Komogorov-Smirnov(K-S) test, are proposed and implemented to compare the speed and flow characteristics between work zone and non work zone conditions. Neither method requires fitting the traffic flow data to specific types of distribution. Using those tools, we further analyzed the mobility characteristics of freeway work zones within the urban area of Milwaukee, WI, USA in 2010. More than 50% of investigated work zones experienced speed drops and about 15-30% also have reduced volumes. Speed drops are more significant within and downstream of the work zones than the upstream of work zones. .
  Authors: Qu, Tao; Jin, Jing; Cheng, Yang; Parker, Steven; Ran, Bin
  Authors: Qu, Tao; Jin, Jing; Cheng, Yang; Parker, Steven; Ran, Bin
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 353
  Paper Number: 13-4561
• Automated Intersection Safety Evaluation Using Linear Referencing System Methods
  Abstract: Effective evaluation of intersection safety requires the ability to develop meaningful benchmarks to help assess the relative safety risk for a given intersection. One approach is to develop a database of average crash rates over intersections with similar features such as functional class, intersection geometry, and, signalization in order to provide a basis for comparison when evaluating specific intersections for potential safety issues. However development and maintenance of such a database requires significant manual effort. This paper introduces an automated intersection safety data collection method, including an algorithm to update intersection crash rates and geometric features from existing sources. The automation algorithm involves the integration of four separate Wisconsin Department of Transportation (WisDOT) databases through association with a common Linear Referencing System (LRS). The result of the application of the automation algorithms suggest the methodology is feasible and can improve the quality of intersection safety data collection. Although the methodology introduced is specific to Wisconsin data, the results can also be applied to other state DOTs that manage traffic data with respect to an LRS.
  Authors: Yang, Fan; Parker, Steven; Wang, Wei; Ran, Bin; Noyce, David A.
  Authors: Yang, Fan; Parker, Steven; Wang, Wei; Ran, Bin; Noyce, David A.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4566
• Intelligent Evaluation of Transportation Management Policies for Metropolitan Areas
  Abstract: Traffic congestion, delay, accident, air and sound pollution are main downsides of living in metropolitans these days. Cities managers are trying to improve life standards in these cities while an important aspect is to reduce traffic and corresponding problems. In this research, expert knowledge is used to identify and organize effective criteria and rank policies for mitigating traffic problems in an overpopulated city. Tehran, the capital of Iran, the biggest city in the Middle East and the 16th dense city in the world is a good example which is studied in this research. To model the policy making problem, significant elements are identified and their weights are calculated and used to prioritize the candidate policies, i.e. bus network improvement, development of subway network, development of road infrastructures and development of bicycle network, using Analytic Hierarchy Process (AHP) based on the knowledge and judgment of a group of experts. Important criteria are classified into clusters of benefits, costs and opportunities in which totally 22 elements form the knowledge tree. Results show that user cost, congestion reduction, fuel consumption and safety approximately form 50 percent of total weight among all studied elements. According to the research conclusion, development of subway networks is the most efficient policy to reduce traffic problems in an overpopulated city as it increases benefits, reduces costs and improves traffic and transport opportunities. Sensitivity analysis shows that development of subway network always remains the superior policy for all relative importance values assigned to benefit, cost and opportunity criteria.
  Authors: Isaai, Mohammad Taghi; Najaf, Pooya; Lavasani, Seyed Mohammad; Nezamianpour Jahromi, Hossein
  Authors: Isaai, Mohammad Taghi; Najaf, Pooya; Lavasani, Seyed Mohammad; Nezamianpour Jahromi, Hossein
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-4610
• Identification of Patterns for Traffic Inputs to Mechanistic-Empirical Pavement Design Guide in New York State
  Abstract: Proper characterization of traffic data is a prerequisite for the determination of appropriate traffic inputs to Mechanistic-Empirical Pavement Design Guide (MEPDG). The objective of the study was to characterize the traffic data and suggest the site-specific, regional or state wide average values for traffic inputs to MEPDG for New York. Vehicle class distribution (VCD), monthly distribution factors (MDF), hourly distribution factors (HDF), average number of axle groups per vehicle (AGPV) and axle load spectra data were obtained from 52 vehicle classification sites and 19 WIM sites in New York State. These traffic data were processed with TrafLoad software. Cluster analysis was adopted for the processed data of VCD, MDF and HDF for the data collected in 2010. This statistical analysis could not be done for AGPV values and axle load spectra due to the unavailability of sufficient number of WIM sites. MEPDG runs were also carried out to investigate the effect of the variability of traffic inputs on the pavement performance of a typical new flexible pavement structure. Cluster specific values were recommended for VCD. Statewide average values were recommended for MDF, HDF, AGPV and axle load spectra.
  Authors: Romanoschi, Stefan A.; Intaj, Ferdous; Bendana, Luis Julian
  Authors: Romanoschi, Stefan A.; Intaj, Ferdous; Bendana, Luis Julian
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-4584
• Motion Prediction Methods for Surrogate Safety Analysis
  Abstract: Despite the rise in interest for surrogate safety analysis, little work has been done to understand and test the impact of the methods for motion prediction which are needed to identify whether two road users are on a collision course and to compute several surrogate safety indicators such as the time to collision (TTC). The default, unjustified method used in much of the literature is prediction at constant velocity. In this paper, a generic framework is presented to predict road users’ future positions depending on their current position and their choice of acceleration and direction. This results in the possibility of generating many predicted trajectories by sampling distributions of acceleration and direction. Three safety indicators, the TTC, an extended version of predicted post encroachment time pPET and a new indicator measuring the probability that the road users attempting evasive actions fail to avoid the collision P(UAE), are computed over all predicted trajectories. These methods and indicators are illustrated on four case studies of lateral road user interactions. The evidence suggests that the prediction method based on the use of a set of initial positions seems to be the most robust. The last contribution of this paper is to make all the data and code used for this paper available (the code as open source) to enable reproducibility and to start a collaborative effort to compare and improve the methods for surrogate safety analysis.
  Authors: Mohamed, Mohamed Gomaa; Saunier, Nicolas
  Authors: Mohamed, Mohamed Gomaa; Saunier, Nicolas
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4647
• Traffic Indicators and Accidents: Case of Motorway Network in the South of France
  Abstract: The purpose of this paper is to study traffic conditions that precede the occurrence of road accidents, and to point out the relation between traffic conditions and accidents.It is to combine traffic variables into indicators; then to constitute different sets of traffic conditions and accidents; and, according to the obtained results, to highlight the variations in the accident risk according to different categories of analysis; and finally to propose to use some indicators in certain contexts in order to predict potential danger, and then warn drivers.Here a traffic database (including individual speeds and headway) is analyzed in relation with the accidents occurred. The proportion of vehicle-kilometers when an accident occurs, in the case of high values of the indicator, has been matched with the same proportion in the case of low values. A tentative to take into account changes in kinematics variables due to local conditions and traffic conditions has been made. The results contribute to validate the link between accident and some indicators, based on occupancy, speed and relative speed.KeywordsIndividual traffic data, accident, surrogate data, traffic indicators, motorway, odd-ratio
  Authors: Aron, Maurice; Seidowsky, Régine; DITCHI, Nicolas
  Authors: Aron, Maurice; Seidowsky, Régine; DITCHI, Nicolas
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4638
• Network Structure and Travel Time Perception
  Abstract: The purpose of this research is to test the systematic variation in the perception of travel time among travelers and relate the variation to the underlying street network structure. Travel survey data from the Twin Cities metropolitan area (includes the cities of Minneapolis and St. Paul) is used for the analysis. Travelers are classified into two groups based on the ratio of perceived and estimated commute travel time. The measures of network structure are estimated using the street network along the identified commute route. T-test comparisons are conducted to identify statistically significant differences in estimated network measures between the two traveler groups. The combined effect of these estimated network measures on travel time is then analyzed using regression models. The results from the t-test and regression analyses confirm the influence of underlying network structure on the perception of travel time.
  Authors: Parthasarathi, Pavithra; Levinson, David M.; Hochmair, Hartwig
  Authors: Parthasarathi, Pavithra; Levinson, David M.; Hochmair, Hartwig
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 733
  Paper Number: 13-4696
• Consumer Behavior and Travel Choices: A Focus on Cyclists and Pedestrians
  Abstract: This paper aims to examine the links between consumer behavior and the mode of transportation used to access local destinations with the greater goal of providing the empirical evidence needed to inform decision making and educate the public. The findings presented here are the result of the first study of this type and scale in the United States. We limit our scope to the examination of the relationships between consumer expenditures and their trip making behavior, including mode of travel and frequency of trips. This analysis is guided by the following objectives: 1) quantifying the various transportation mode shares of customers for a variety of business types, locations and transportation contexts; and 2) comparing levels of consumer spending & frequency of visits by travel modes. This analysis made use of intercept surveys of local business completed at 78 establishments in the Portland metropolitan area. The findings support the notion that customers that arrive by modes other than the automobile are competitive consumers, spending similar amounts or more, on average, than their counterparts using automobiles. They are also more frequent patrons on average, presenting perhaps a unique marketing opportunity for these businesses.
  Authors: Clifton, Kelly J.; Currans, Kristina Marie; Muhs, Christopher; Ritter, Chloe; Morrissey, Sara; Roughton, Collin
  Authors: Clifton, Kelly J.; Currans, Kristina Marie; Muhs, Christopher; Ritter, Chloe; Morrissey, Sara; Roughton, Collin
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists; Planning and Forecasting
  Session: 735
  Paper Number: 13-4743
• Forecasting of Short-Term Urban Rail Transit Passenger Flow with Support Vector Machine Hybrid Online Model
  Abstract: Prediction for short-term urban passenger rail flow is essential for effective urban rail transit operation and management. It is important for a forecasting model to capture the periodicity and nonlinearity of short-term passenger flow and to embed these characteristics into the model to enhance forecasting performance. In this research, a support vector machine global online model (SVMGOL) is first proposed by embedding the periodic characteristics via SARIMA model to capture the inherent periodicity of passenger flow. A support vector machine local online model (SVMLOL) is then proposed by embedding the nonlinear characteristics via successive passenger flow value inputs to capture the local nonlinear characteristics of the passenger flow. To take advantage of the two online models, this research then constructs a support vector machine hybrid online model (SVMHOL) based on the idea of data fusion. The model building process and its application in the prediction of short-term passenger flow at Zhujianglu Station of Nanjing Metro is discussed. Testing results show that for the one-step forecasting, the SVMHOL model outperforms the individual SARIMA or SVM model in terms of mean absolute error, mean absolute percent error and root mean square error.
  Authors: Zhang, Ning; Zhang, Yunlong; Wang, Xuemei
  Authors: Zhang, Ning; Zhang, Yunlong; Wang, Xuemei
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-4393
• Development of Connectivity-Based Underground Fiber-Optic NetworkInventory Systems
  Abstract: Major State Departments of Transportation such as the New Jersey Department of Transportation (NJDOT) operate and maintain networks of thousands of miles of conduits, many carrying fiber optic cables that are vital to State communication systems. These conduits are located alongside or across highways and frequently must be located and marked to avoid damage from digging or boring resulting from construction. The existing inventory system consisted of sections of pipelines of varying length with differing lengths and sometimes unknown or changing diameters and materials. In order to facilitate the location of fiber optic facilities by operations personnel and enable access to junction boxes and conduits, a computerized connectivity-based inventory system for fiber optic segments and nodes (junction boxes) was developed in a first phase. The system enabled the transition from a flat incomplete and inaccurate system of facility identification to a comprehensive hierarchical system of facility cataloguing. An expansion of the system to include multiple inner layers within pipes and junction boxes, such as Conduits and Cables enabled the definition of a Routing entity, an essential component of a comprehensive fiber optic connectivity-based system. Key to the system design is the definition of the multi-layered hierarchical relationships between various levels of facility definition. The ability to “drill-down” from an external layer to an inner component and to establish multi-directional facility contiguity enables the progressive improvement of data quality and the establishment of a reliable connectivity model between facilities. This extended prototype enables the successful transition from a system based on section records to a more connectivity-based hierarchical asset management model of fiber optic underground facilities, with significant savings in operational costs and reliability of the field investigative work.
  Authors: Karaa, Fadi Antoun; Banerji, Sugata
  Authors: Karaa, Fadi Antoun; Banerji, Sugata
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 618
  Paper Number: 13-4448
• Semantic Annotation of GPS Traces: Activity Type Inference
  Abstract: Due to the rapid development of technology, increasingly larger travel and activity behavior data exists to date. These large data sets often lack semantic interpretation, implying that annotation in terms of the activity being performed or the transportation mode being used is necessary. This paper aims to infer activity types from GPS traces by developing a decision tree-based model that considers activity start times and activity durations. Two models, i.e. a predicted probability distribution and a point prediction model, were derived from a decision tree classification. Two types of data were used, namely paper-and-pencil activity-travel diary data and corresponding GPS data. The data were collected in 2006 and 2007 in Flanders, Belgium. The most optimal classification tree constructed when considering both in-home and out-of-home activities comprises 18 leaves. Consequently, 18 if-then rules were derived. An accuracy of 74% was achieved when training the tree. The accuracy of the model for the validation set, i.e. 72.5%, shows that overfitting is minimal. When applying the model to the test set, the performance was almost 76% accurate. Based on the decision tree, a probability matrix was constructed. From this probability matrix, a point prediction was extracted using the highest probabilities per class. The models constructed indicate the importance of time information in the semantic enrichment process. The contribution of this study towards future data collection is promising in that it enables researchers to automatically infer activities solely from activity start time and duration information obtained from GPS data.
  Authors: Reumers, Sofie; Liu, Feng; Janssens, Davy; Cools, Mario; Wets, Geert
  Authors: Reumers, Sofie; Liu, Feng; Janssens, Davy; Cools, Mario; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 791
  Paper Number: 13-4496
• Characterizing Walk Trips in Communities by Using Data from 2009 National Household Travel Survey, American Community Survey, and Other Sources
  Abstract: Non-motorized travel (i.e. walking and bicycling) are of increasing interest to the transportation profession, especially in context with energy consumption, reducing vehicular congestion, urban development patterns, and promotion of healthier life styles. This research project aimed to identify factors impacting the amount of travel for both walk and bike trips at the Census block group or tract level, using several public and private data sources. The key survey of travel behavior is the 2009 National Household Travel Survey (NHTS) which had over 87,000 walk trips for persons 16 and over, and over 6000 bike trips for persons 16 and over. The NHTS, in conjunction with the Census Bureau’s American Community Survey, street density measures using Census Bureau TIGER, WalkScore®, Nielsen Claritas employment estimates, and several other sources were used for this study. Stepwise Logistic Regression modeling techniques as well as Discriminant Analysis were applied using the integrated data set. While the models performed reasonably well for walk trips, travel by bike was abandoned due to sparseness of data. This paper discusses data sources utilized and modeling processes conducted under this study. It also presents a summary of findings and addresses data challenges and lesson-learned from this research effort.
  Authors: Hwang, Ho-Ling; Reuscher, Timothy; Wilson, Daniel W.; Murakami, Elaine
  Authors: Hwang, Ho-Ling; Reuscher, Timothy; Wilson, Daniel W.; Murakami, Elaine
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Pedestrians and Bicyclists
  Session: 425
  Paper Number: 13-4509
• Examining Heterogeneity of Driver Behavior Using Temporal and Spatial Factors
  Abstract: Temporal and spatial characteristics of the road environment are known to influence driver behaviour and consequently the risk of an injury or fatality crash. Nonetheless, much of our understanding of the risks of injury and fatality associated with driving relies heavily on police crash records. These capture the most serious of crashes but underreport other events. Studies which rely on these data sources typically ignore the temporal and spatial factors. Advances in technology have enabled more detailed study of driving on a day-to-day basis and therefore the opportunity to examine driver behaviour for the same driver across time and space. However, this has brought with it its own difficulties. This includes extensive intra and inter-driver heterogeneity which is not apparent when using ‘traditional’ data collection methods. This paper presents a framework and methodology for isolating the influence of drivers’ inherent characteristics on driver behaviour. This is done by constructing temporal and spatial identifiers which control for the influence of the road environment. Results of analyses conducted using empirical driving information collected from 106 vehicles in Sydney, Australia to examine the effectiveness of this approach are included. The results indicate that in 80 percent of road environments there is less intra-driver variability in speeding behaviour than inter-driver variability when accounting for temporal and spatial characteristics. Clustering and regression analyses for the most frequently observed road environments are also presented. Further work is necessary to establish the extent to which these results apply across datasets with different characteristics.
  Authors: Ellison, Adrian B.; Greaves, Stephen; Bliemer, Michiel
  Authors: Ellison, Adrian B.; Greaves, Stephen; Bliemer, Michiel
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4541
• Crash Databases in Australasia, European Union, and United States: Review and Prospects for Improvement
  Abstract: Since the quality of decision making in road safety is dependent on the quality of the data on which decisions are based, efforts to improve the quality, timeliness and accuracy of crash databases are crucial. To contribute to the scientific debate for the identification of directions for improvement of the existing databases, a critical review of Australasian, EU, and US crash databases has been performed and future directions have been identified. Major issues are related to access procedures to crash data, crash report form, severity of crashes reported in the databases, crash location, crash classification, and crash severity. Access to crash databases might be provided to approved road safety professionals through a web-based portal, providing also the detailed police crash reports. The use of electronic crash report forms is strongly recommended since it might solve most of the problems associated with paper. Severity of crashes reported in the databases vary across the countries and not all the countries report property damage only crashes. However, both PDO and injury crashes might give information on crashes to be prevented and we recommend consistency between the countries in collecting also property damage only crashes and using these crashes to develop safety strategies. Combined use of GPS devices and GIS improves crash location and overcomes the traditional problems in crash location, such as inaccuracies and collection mistakes. To develop effective countermeasures, we recommend to classify crashes by the maneuvers and sequence of events of each traffic unit. The adoption of the same system for crash severity classification in different countries would allow comparisons in the safety performances between countries and jurisdictions.
  Authors: Montella, Alfonso; Andreassen, David; Tarko, Andrew P.; Turner, Shane Alan; Mauriello, Filomena; Imbriani, Lella Liana; Romero, Mario
  Authors: Montella, Alfonso; Andreassen, David; Tarko, Andrew P.; Turner, Shane Alan; Mauriello, Filomena; Imbriani, Lella Liana; Romero, Mario
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4219
• Individual Mobility Attributes and Their Impact on Modality Style: Comparison Across Three Population Sectors in Jerusalem, Israel
  Abstract: Mobility attributes such as driver license, car ownership, reserved parking at work, and transit pass have a very strong impact on travel choices, in particular, mode choice. Mobility attributes are not acquired for a particular trip but are rather driven by the entire set of individual travel needs (commuting being the most basic of them). Some mobility attributes, for example car ownership and transit pass, are substitutable and some other ones, for example, car ownership and reserved parking at work, are complementary. For this reason, different mobility attributes have to be analyzed and modeled jointly.The purpose of the current research is to analyze a wide set of mobility attributes and incorporate them in an operational ABM as a set of mid-term choices. The approach suggested in this paper, is based on an iterative application of three interlinked choice sub-models: 1) joint choice of person driver license, usual driver role (priority in using one of the household cars), car type choice, reserved or reimbursed parking at work, and transit pass, 2) household car ownership choice by type, and 3) intra-household car allocation by type. Model estimation results confirmed strong cross-attribute effects as well as revealed many impacts of person, household, and travel accessibility variables. In particular, historical and cultural differences between 3 population sectors in Jerusalem – Secular Jewish, Orthodox Jewish, and Arab, manifested themselves very strongly. Application of these models for future scenarios and incorporation of dynamic trends is discussed.
  Authors: Vovsha, Peter; Vyas, Gaurav; Givon, Danny; Birotker, Yehoshua
  Authors: Vovsha, Peter; Vyas, Gaurav; Givon, Danny; Birotker, Yehoshua
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4325
• Measuring Serious Injuries in Traffic Crashes
  Abstract: The Moving Ahead for Progress in the 21st Century Act (MAP-21) legislates highway safety performance metrics that consider serious injuries in addition to fatalities in crashes. To assess serious injuries, states will need better ways of measuring seriously injured occupants than are typically available. The best method of assessing injury level is direct linkage between crash, EMS, and hospital databases. However, in the near term states have to rely on existing crash data, which typically have limited injury severity information. This paper summarizes work on injury severity coding systems, measures of injury severity, and definitions of serious injury. Ideal metrics have three characteristics: 1) predictive of threat-to-life, 2) wide availably, and 3) easy of use. Three injury-coding systems are discussed, including the Abbreviated Injury Scale (AIS), the police-reported injury coding system (KABCO), and the International Classification of Disease (ICD). The crash community has general consensus that the maximum AIS score of 3 or more (MAIS 3+) is the preferred definition of serious injury.Because state crash datasets lack detailed injury coding, we explored using KA (killed and incapacitating) injuries as a near-term substitute for MAIS 3+. The relationship between KABCO and both fatality and serious injury is strong, but KA overestimates the number of serious injuries by about 3 times. Adding information about EMS transport did not improve performance, but hospitalization information did. We conclude that while direct linkage systems are being developed at the state level, KA adjusted for overcounting is a reasonable estimator of serious injuries in crashes.
  Authors: Flannagan, Carol A.; Mann, Clay; Rupp, Jonathon
  Authors: Flannagan, Carol A.; Mann, Clay; Rupp, Jonathon
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4780
• Framework for Automatic Identification and Extraction of Travel Lane Information from Georectified Aerial Images Using Support Vector Machine
  Abstract: Travel lane data such as number of lanes and lane width are basic input to many transportation studies. Traditionally, these data are either collected in the field or are manually extracted from aerial images. These methods of data acquisition are both resource intensive and slow, especially when large study areas are involved. The availability of high-resolution geo-rectified aerial images provides an inexpensive alternative to acquiring these data via automatic extraction methods. This paper presents a framework for automatically identifying and extracting travel lane data from geo-rectified aerial images using a classification technique known as Support Vector Machine (SVM). Five-folder cross-validation was applied to a test location in Miami-Dade County in Florida, where 490 instances were extracted from real-world data. The binary classification test shows that SVM with the polynomial kernel and the Radial Basis Function (RBF) kernel both gave ideal accuracy. In a sample test with a lane profile model consisting of 13 features, both the polynomial kernel with exponent higher than three and the RBF kernel with ? larger than 1 provided a precision rate of higher than 90%. The accuracy statistics indicate that it is feasible to identify complete travel lane profiles from geo-rectified aerial images with the proposed framework.
  Authors: Tang, Li; Gan, Albert; Alluri, Priyanka
  Authors: Tang, Li; Gan, Albert; Alluri, Priyanka
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-4786
• Assessing the Impacts of Energy Developments on Rural Texas Highway Infrastructure
  Abstract: While recent energy developments have been a boon for the Texas economy, the rush to develop oil and gas resources has taken a toll on low-volume roads throughout the state. The impacts of heavy truck traffic on roadway infrastructure in the Eagle Ford Shale and Barnett Shale plays are obvious in the cracks, potholes, and other major distresses that manifest in pavements throughout these areas. Many of Texas’ Farm-to-Market, Ranch-to-Market, and local county roadway systems are not designed to withstand the heavy loads arising from energy resource development. Rapid energy resource exploitation will continue to strain agencies responsible for maintaining and preserving roadways until measures are taken to implement infrastructure impact plans, road-user agreements, or other measures to obtain compensation for damage from heavy haulers.This paper explores three approaches for partnership between energy companies, county officials, and other organizations. The proactive, performance-based approach strengthens pavements prior to energy development. The reactive, performance-based approach assesses impact fees associated with road maintenance after the damage. The third approach assesses impact fees that are not attached to actual roadway deterioration. The authors discuss what is currently being done in Texas and suggest recommendations for future work. With future exploration and development expected throughout Texas and in other regions of the United States, execution of roadway use agreements will be critical to maintaining adequate levels of service and preserving strong working relationships between the energy industry and county governments charged with preserving roadway assets.
  Authors: Miller, Timothy D.; Sassin, James M.
  Authors: Miller, Timothy D.; Sassin, James M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Energy; Pavements
  Session: 534
  Paper Number: 13-4834
• Bayesian Inference of Traffic Volumes Based on Bluetooth Data
  Abstract: The study of the relationship between macroscopic traffic parameters, such as flow, speed and travel time, is essential to the understanding of the behaviour of freeway and arterial roads. However, the temporal dynamics of these parameters are difficult to model, especially for arterial roads, where the process of traffic change is driven by a variety of variables. The introduction of the Bluetooth technology into the transportation area has proven exceptionally useful for monitoring vehicular traffic, and Bluetooth data is now being used for travel time estimations and as a novel approach for studying traffic demand.In this work, we propose an approach based on Bayesian networks for analyzing and predicting the complex dynamics of flow or volume, based on travel time observations from Bluetooth sensors. The spatio-temporal relationship between volume and travel time is captured through a first-order transition model, and a univariate Gaussian sensor model. The two models are trained and tested on travel time and volume data, from an arterial link, collected over a period of six days. To reduce the computational costs of the inference tasks, volume is converted into a discrete variable. The discretization process is carried out through a Self-Organizing Map.Preliminary results show that a simple Bayesian network can effectively estimate and predict the complex temporal dynamics of arterial volumes from the travel time data. Not only is the model well suited to produce posterior distributions over single past, current and future states; but it also allows computing the estimations of joint distributions, over sequences of states. Furthermore, the Bayesian network can achieve excellent prediction, even when the stream of travel time observation is partially incomplete.
  Authors: Nantes, Alfredo; Billot, Romain; Miska, Marc Philipp; Chung, Edward
  Authors: Nantes, Alfredo; Billot, Romain; Miska, Marc Philipp; Chung, Edward
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-4838
• Know Your Audience: Conducting Effective Travel Diary Surveys at Colleges and Universities
  Abstract: Despite being frequently underrepresented in travel diary survey efforts, colleges and universities – depending on their size, geographic location, and student body composition – can be major contributors to travel demand in their respective regions; therefore, researchers ought to study travel patterns and behavior at these educational institutions more often and in greater detail. This paper uses two case studies to detail the approach, design, and methodology of conducting travel diary surveys at colleges and universities. The first case study focuses on one stand-alone travel diary of students, faculty, and staff at Arizona State University, one of the largest universities in North America. The data collected (14,464 valid responses) will help support the Maricopa Association of Governments’ activity-based travel demand model. The second case study examines the survey administered at eight colleges (7,923 valid responses in total) across the state of Utah that was linked to the larger statewide household diary survey. This paper highlights the similarities and differences between the two approaches, notes the relative cost-effectiveness of both methodologies, and discusses the value of these datasets to regional travel demand modelers and strategic planners at educational institutions.
  Authors: Kerrigan, James; Greene, Elizabeth R; Pendyala, Ram M.
  Authors: Kerrigan, James; Greene, Elizabeth R; Pendyala, Ram M.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 615
  Paper Number: 13-4843
• Identification of Crash Contributing Factors: Effects of Spatial Autocorrelation and Sample Data Size
  Abstract: This paper uses sample sets of crash data to examine the similarities in crash contributing factors among various counties that have similar effects on spatial autocorrelation (SA). Moran’s I and Getis-Ord Gi* statistics were used to determine the correlation, and the multinomial logistic regression to identify the crash contributing factors. Seventy-five counties in the state of Arkansas were divided into five categories based on the Z-values of the Getis-Ord Gi* statistic. Depending on the sample size, crash data from a county or a group of counties from each of these categories were used, and factors contributing to crashes in each of the categories were identified based on the crash severity index. Results indicated that most of the crash contributing factors identified for each category were also identified by the crash data from a county or a group of counties in that category. Pulaski county, with the highest Z-value from the first category indicated largest cluster of crashes and identified the highest percentage (55%) of factors that contributed to crashes in that category using sample crash data. From the sample data used, the multinomial logistic regression indicated the following factors to be positively associated with crash severity: nighttime driving, driving under the influence of alcohol, roadway gradient, curved alignment, rural areas, and head-on and sideswipe-same direction collision types. The results of this research can be used for better allocation of funds by departments of transportation to identify crash contributing factors that are associated with higher levels of crash severity by analyzing smaller sets of data.
  Authors: Manepalli, Uday Raghavender Rao; Bham, Ghulam Hussain
  Authors: Manepalli, Uday Raghavender Rao; Bham, Ghulam Hussain
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4846
• Using GPS Data to Calculate Delay Time on Classified Roads in Houston-Galveston-Brazoria Area
  Abstract: Congestion is an ongoing issue in the Houston-Galveston-Brazoria area. Until recently, traffic analyses were conducted by manual vehicle counts, videotaping and other dated methods that resulted in inaccurate results. This research focuses on using GPS data to calculate delay time on classified roads in the HGB region. GPS devices provide local time and date, location, speed, and elevation at one second intervals. This type of data is a more accurate method of analyzing traffic volume because it (1) analyzes a complete route and (2) focuses on exact times and locations. With the availability of second-by-second speed, acceleration and deceleration trends can be established and delay duration can be analyzed.The primary objective of this research is to analyze traffic volume and calculate delay time on major freeways in the HGB area. This research is a pilot test, thus minimal data was acquired. A more in depth study will be conducted in the near future that is aimed to calculate delay time on all of the major freeways in the HGB area.
  Authors: Hoover, Chelse
  Authors: Hoover, Chelse
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-4858
• Investigating the Characteristics of Secondary Crashes on Freeways
  Abstract: Prevention of secondary crashes is one of the priorities in traffic incident management. However, limited information on secondary crashes has largely impeded the selection of appropriate countermeasures. The primary goal of this paper is to improve the understanding of secondary crashes, which is achieved by two major steps. First, an analysis framework is developed to accurately identify secondary crashes by integrating rich traffic sensor data with the statewide crash data sets. Second, the characteristics of the identified secondary crashes are investigated in detail. Secondary crashes that occurred on a 27-mile section of a major highway in New Jersey were mined using the proposed analysis framework. A thorough examination of their characteristics was then performed. Empirical findings on the frequency of secondary crashes, their spatio-temporal distributions, clearance time, crash type, severity, and major contributing factors were highlighted. These preliminary results can help transportation agencies make more informed decisions on mitigating secondary crashes and improve their incident management operations. To complement the results, further in-depth investigations based on more high-resolution sensor data and high-quality incident records are suggested.
  Authors: Yang, Hong; Bartin, Bekir; Ozbay, Kaan
  Authors: Yang, Hong; Bartin, Bekir; Ozbay, Kaan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4866
• Fully Bayesian Before-After Evaluation of Traffic Safety Improvements in the City of Edmonton, Canada
  Abstract: The objective of this study is to evaluate the safety performance of a sample of intersections that have been improved with the implementation of certain safety countermeasures targeting right-turn (RT) collisions in the City of Edmonton. A full Bayes approach is utilized to determine the effectiveness of the improvements using a before-after design with matched (yoked) comparison groups. Three linear intervention models were considered: a multivariate model which modeled treatment effects as a gradual change, a similar model but with the addition of a jump treatment effect, and a univariate model analyzing specifically right-turn collisions. The results indicate that the safety improvement program was effective, reducing up to 40% of right-turn collisions. Despite the small sample size, these reductions were statistically significant. The results show the usefulness of the FB technique in performing before and after evaluations of traffic treatment programs, absolving the need of a reference population and also allowing for far more different types of analysis, including multivariate analysis (modelling collisions of different types and severities at the same time), temporal effects (for both treatment and long term trends), and greater freedom in selection of error structure.
  Authors: Li, Simon; Sayed, Tarek; El-Basyouny, Karim
  Authors: Li, Simon; Sayed, Tarek; El-Basyouny, Karim
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4869
• Evaluating the Performance of Travel Time Outlier Detection Algorithms
  Abstract: A number of technologies are available to acquire vehicle travel times including automatic number plate recognition (ANPR), cell phone probes, dedicated GPS probes, automatic identification of vehicles equipped with transponders or toll tags, and Bluetooth detectors. The travel time measurements from all of these technologies contain various sources of errors and biases. As a result, a number of filtering and outlier detection algorithms have been proposed to identify erroneous data and exclude them from the analysis. However, it is difficult to assess the performance of a given outlier detection algorithm in either absolute terms or with relative to any other algorithm using field data because the true travel times are unknown. Furthermore, it is not possible to identify how well the algorithm can identify any given source of outliers.In this paper we propose a framework for evaluating travel time outlier detection algorithms. The framework can be customized to address the specific characteristics of any travel time sensor technology. However, in this paper we demonstrate the framework for application to travel times acquired by Bluetooth detectors on arterial roadways. We use the framework to evaluate the performance characteristics of two outlier detection algorithms proposed by Dion and Rakha. The results clearly show the performance characteristics of both algorithms for a wide range of operating conditions. It is demonstrated that one of the algorithms has an approximately 30% likelihood of providing results that are worse than not using any outlier detection algorithm at all. The other algorithm is shown to provide improvements under almost all conditions with a relative improvement of up to 60%.
  Authors: Salek Moghaddam, Soroush; Hellinga, Bruce
  Authors: Salek Moghaddam, Soroush; Hellinga, Bruce
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-4932
• Feasibility of Using Cellular Phone Location Data in Traffic Survey on Intercity Trips
  Abstract: This research analyzed the feasibility of using cell phone locations data for collecting traffic data on inter-city trips. Cell phone positioning technologies and their penetration rates, as well as the limitations of their applications, were discussed. Algorithms for collecting traffic data between cities are proposed on the basis of the network-based cell phone location data. A cell phone location database including cities located along the Kansas Metro Corridor was used to estimate daily traffic, derive the origin-destination (O-D) traffic by time-of-day and commuting traffic along the corridor based on a five week observation period. The results found that the available cell phone network data detected about 15 percent of the daily traffic data compared to the Average Annual Daily Traffic (AADT) data along the Kansas Metro Corridor. It was also found that using the cell phone network can not only estimate a portion of ground traffic volumes, but also can reflect the variety of traffic flow due to special events. The results found that the use of cell phone network data in estimating the dynamic O-D traffic flow can reflect similar trends in actual commuting traffic on inter-city trips. Nevertheless, including more network data from other carriers and applying the appropriate data verification are needed for further study.
  Authors: Wang, Ming-Heng; Schrock, Steven D.; Vander Broek, Nate; Mulinazzi, Thomas
  Authors: Wang, Ming-Heng; Schrock, Steven D.; Vander Broek, Nate; Mulinazzi, Thomas
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-4957
• Are Transit Trips Symmetrical in Time and Space? Evidence from Twin Cities, Minnesota
  Abstract: In this study we exploit electronic fare collection data to examine the symmetry of boardings and alightings along a transit route. The symmetry of boardings and alightings is arguably the most important concept in estimating travel distance such as average trip lengths and passenger miles from entry-only fare collection system data. We show how such data can be used to examine the symmetry of boardings and alightings through travel patterns in spatial and temporal dimensions. A novel method for aggregating stops, especially for the nearest stops(s) in the opposite direction, is used to compare boardings in one direction with alightings in the opposite direction. Spatially, the method allows us to examine the characteristics of boardings and alightings in a spatial dimension. Temporally, we examine whether a specific and symmetric passenger flow is observed between any specific time periods (e.g., between AM and PM peaks). A case study of the Minneapolis-St. Paul region is performed using automatically collected data from Metro Transit.
  Authors: Lee, Sanggu; Hickman, Mark D.
  Authors: Lee, Sanggu; Hickman, Mark D.
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 731
  Paper Number: 13-4985
• Real-Time Identification of Crash-Prone Traffic Conditions Under Different Weather on Freeways
  Abstract: Understanding the relationships between traffic flow characteristics and crash risk under adverse weather conditions will help highway agencies develop proactive safety management strategies to improve traffic safety in adverse weather conditions. The primary objective of this study is to develop separate crash risk prediction models for different weather conditions. The crash data and traffic data used in this study were collected on the I-880N freeway in California, United States in 2008 and 2010. This study considers three different weather conditions: clear weather, rainy weather and reduced visibility weather. The preliminary analysis showed that there was some heterogeneity in the risk estimate for traffic flow characteristics by weather conditions, and that the crash risk prediction model for all weather conditions cannot capture the impacts of the traffic flow variables on crash risk under adverse weather conditions. The Bayesian logistic regressions were applied in this study to link the likelihood of crash occurrence with various traffic flow characteristics under different weather conditions. The model estimation results showed that the traffic flow characteristics contributing to crash risk were found to be different across different weather conditions. The speed difference between upstream and downstream station was found to be significant in each crash risk prediction model. And the large speed difference between upstream and downstream station in reduced visibility weather has the largest impacts on crash risk, followed by that in rainy weather. The ROC curves were further developed to evaluate the prediction performance of the crash risk prediction model under different weather conditions. It was found that the prediction performance of the crash risk model for clear weather was better than that of the crash risk model for adverse weather condtions.
  Authors: Xu, Chengcheng; Wang, Wei; Liu, Pan; Jiang, Xuan; Li, Zhibin; Zhang, Xin
  Authors: Xu, Chengcheng; Wang, Wei; Liu, Pan; Jiang, Xuan; Li, Zhibin; Zhang, Xin
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4996
• Development of Statistically Based Methodology for Analyzing Safety Treatments at Isolated High-Speed Signalized Intersections
  Abstract: Crashes at isolated, rural intersections, particularly those involving vehicles traveling perpendicular to each other, are particularly bad because of high speeds involved. Many transportation agencies are interested in reducing the number of crashes at these types of intersections. There are many engineering treatments to improve the traffic safety at isolated, high-speed signalized intersections. Intuitively, it is critical to know which safety treatment may be the most effective for a given set of selection criteria for a particular intersection. Without a well-defined decision methodology it is almost impossible to decide which safety countermeasure or a set of countermeasures would the best option. Additionally because of the very large number of possible intersection configurations as well as the varying amount, distribution and type of traffic, it would be impossible to develop a set of guidelines that could be used for all signalized intersections. Therefore, it was undertaken to develop a methodology whereby common countermeasures could be modeled and analyzed before being implemented in the field. Because of the dynamic and stochastic nature of the problem it was decided to employ microsimulation tools, such as VISSIM, for analyzing the countermeasures. A calibrated and validated microsimulation model of signalized intersection was used to model two common safety countermeasures. The methodology was demonstrated on a test site located just outside of Lincoln, Nebraska. The model was calibrated to the distribution of observed speeds collected at the test site. It was shown that the methodology could be used for the preliminary analysis of the safety treatments.
  Authors: Wojtal, Remigiusz Marcin; Rilett, Laurence Russell
  Authors: Wojtal, Remigiusz Marcin; Rilett, Laurence Russell
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-5070
• Consideration of Shale Gas Development Impacts in Long-Range Transportation Planning
  Abstract: Through the combination of two technologies—horizontal drilling and hydraulic fracturing- the U.S. natural gas industry has been able to access vast quantities of gas in tight shale formations. Shale gas development has had and will continue to have impacts on the performance of the transportation system—directly through increased heavy truck traffic and freight rail movement to supply equipment, water and chemicals, and indirectly through increased employment, that in turn generates additional travel demand. The purpose of this study was to review the state of the practice for considering shale gas impacts in long-range transportation planning. Recent statewide, metropolitan and rural transportation plans in areas already undergoing shale gas development in Texas, Pennsylvania, West Virginia and Ohio were reviewed. The review showed that qualitative acknowledgement of shale gas impacts on transportation is being included in some recently updated long-range plans, but the level of coverage of this issue varies substantially in different locations. Most long-range plans are not yet addressing shale gas impacts on safety, congestion or transportation-related air pollutant emissions. Potential approaches to improving the consideration of shale gas impacts in transportation planning include build-out analyses to generate potential well pad locations and enable prediction of impacts on specific roadways and system-wide indicators such as vehicle miles traveled. Further research and guidance is needed to provide a workable framework for transportation planning organizations to meaningfully address shale gas development in the long-range planning process.
  Authors: Tidd, Leo
  Authors: Tidd, Leo
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Energy; Pavements
  Session: 534
  Paper Number: 13-5115
• Panel Mixed Ordered Probit Fractional Split Model: Modeling Vehicle Speed on Urban Roads in Montreal, Canada
  Abstract: Vehicle operating speed measured on roadways is a critical ingredient for a host of analysis in the transportation field including transportation safety, traffic flow, geometric design, vehicle emissions, and road user route decisions. The current research effort contributes to literature on examining vehicle speed on urban roads methodologically and substantively. In terms of methodology, we formulate a new econometric model framework for examining speed profiles. The proposed model is an ordered response formulation of a fractional split model. The ordered nature of the speed variable allows us to propose an ordered variant of the fractional split model. The proposed formulation allows us to model the proportion of vehicles traveling in each speed range for the entire segment of roadway. Further, we employ a mixed version of the fractional split model to account for the influence of site-specific unobserved effects. The paper contributes substantively by estimating the proposed model using a unique dataset from Montreal consisting of weekly speed data (collected in hourly intervals) for about 50 local roads and 70 arterial roads. We estimate separate models for local roads and arterial roads. The model estimation exercise considers a whole host of variables including geometric design attributes, roadway attributes, traffic characteristics and environmental factors. The model results highlight the role of various street characteristics including number of lanes, presence of parking, presence of sidewalks, vertical grade, and bicycle route on vehicle speed proportions. The results also highlight the presence of site-specific unobserved effects influencing the side walk variables as well as the standard deviation on the propensity constant. The parameters from the modeling exercise are validated using a hold-out sample not considered for model estimation. The results indicate that the proposed panel mixed ordered probit fractional split model offer promise for modeling such proportional ordinal variables.
  Authors: Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis Fernando
  Authors: Eluru, Naveen; Chakour, Vincent; Chamberlain, Morgan; Miranda-Moreno, Luis Fernando
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Operations and Traffic Management; Safety and Human Factors
  Session: 658
  Paper Number: 13-5141
• Simplified Truck Traffic Classification Groupings for DARWin-ME
  Abstract: Traffic loads obtained using automated traffic collection techniques such as Weight-In-Motion (WIM) are one of the key data elements required in the Mechanistic-Empirical Pavement Design Guide (MEPDG) and the subsequent DARWin-ME. Due to the limited number of WIM stations within a state agency, a key to the successful use of WIM traffic data in the new design guide is to be able to recognize traffic loading clusters so as to estimate the full axle load spectrum data occurring at a particular site. Even though various clustering approaches have been proposed, they are either computationally extensive or requiring site-specific truck count data. In most cases for designing new pavements, site-specific traffic data are not available before a pavement is open to the traffic; therefore it is desirable to develop a simplified truck grouping technique for DARWin-ME design when such information is missing. Following the Truck Traffic Classification (TTC) concept in DARWin-ME, K-Means cluster analysis algorithm is applied using the historical WIM data from Arkansas Highway Transportation Department (AHTD) and simplified TTC clusters are developed. Traffic input data generated based on DARWin-ME TTC grouping and simplified cluster approach are compared and analyses conducted. A case study is provided to demonstrate the applicability of using the simplified clusters to generate Level 2 traffic inputs for DARWin-ME design. The simplified TTC grouping method developed in the paper only requires prior knowledge of the trucking patterns that occur on specific roads and will alleviate the preparation of the traffic load spectra inputs based on WIM data for the new design guide procedure.
  Authors: Wang, Kelvin C. P.; Li, Qiang; Nguyen, Vu T. D.; Qiu, Shi; Zhang, Zhongjie; Moravec, Michael M
  Authors: Wang, Kelvin C. P.; Li, Qiang; Nguyen, Vu T. D.; Qiu, Shi; Zhang, Zhongjie; Moravec, Michael M
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 610
  Paper Number: 13-5238
• Shifting Sands: Emerging Transportation Impacts of Frac Sand Mining and Shale Gas Drilling
  Abstract: Damage to roads is an impact of the emerging industry of shale gas drilling and frac sand mining. County governments have used a number of mechanisms to recover the costs of road damage. Chippewa County, Wisconsin serves as a model of how local governments are using road use agreements to recover road damages, fund maintenance, and expedite grade crossing improvements. This paper examines Chippewa County’s road use agreements and discusses the implications for neighboring counties, state-level policy and the need for a regional approach to assigning impacts.
  Authors: Hart, Maria; Adams, Teresa M.; Schwartz, Andrew
  Authors: Hart, Maria; Adams, Teresa M.; Schwartz, Andrew
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Energy; Pavements
  Session: 534
  Paper Number: 13-5245
• Using Smart Phones and Sensor Technologies to Automate Collection of Travel Data
  Abstract: This paper presents a comprehensive framework and its prototype application for activity-travel data collection through the exploitations of smartphone sensors. The core components of the framework run on smartphones, backed by cloud-based services for data storage, information dissemination and online decision support. The framework employs machine learning techniques to automatically infer activity types and travel modes with minimum interruptions for the respondents. There are three main components of the framework: 1) a 24 hours location data collection, 2) a dynamic land-use database, and 3) a transportation mode identification component. The location logger is based on the smartphone network and it can run for 24 hours with minimum impact on smartphone battery and equally applicable in places where GPS is available or not available. The land-use information is continuously updated from internet location services such as Foursquare. Transportation mode identification module is able to distinguish six different modes with 98.85% accuracy. Prototype application is conducted in the city of Toronto and results clearly indicate the viability of this framework.
  Authors: Abdulazim, Tamer; Abdelgawad, Hossam; Nurul Habib, Khandker M.; Abdulhai, Baher
  Authors: Abdulazim, Tamer; Abdelgawad, Hossam; Nurul Habib, Khandker M.; Abdulhai, Baher
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Planning and Forecasting
  Session: 791
  Paper Number: 13-5254
• Real-Time Sight Distance and Road Surface Calculations via the Wavefront Topology Algorithm
  Abstract: The Wavefront Topology System (WTS) is a novel 3D tessellation algorithm. The WTS algorithm is extended to applications in navigation and highway design models. The WTS road surface navigation algorithm determines sight distance, center lines, and road geometry; information on surface slope is inferred from the process. The algorithm processes road surface data from video images. Road geometry is calculated through an iterative procedure which involves comparing WTS coordinate nodes to the lane boundaries. The lane delimiters are segmented with the assistance of an edge detection filter. The geometric structure of the road surface is extracted with a region filling process. Once the surface domain is filled with WTS coordinate nodes, then additional road properties are calculated. The maximum distance and angle of the sight line vector is computed for each road surface corresponding to an image frame. A virtual field of view (FOV) facilitates determination of road profiles and local slopes. The intersection of the WTS nodes with the field of view x-y plane provides an interpretation of slope maxima and minima. The center line elements are determined from the WTS boundary nodes. Each WTS node is a data structure that contains Cartesian coordinates and links to its adjacent points.
  Authors: Thomas, Clayton; Jha, Manoj K.
  Authors: Thomas, Clayton; Jha, Manoj K.
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-5278
• Car-Following Trajectory Modeling with Machine Learning: Showcase for Merits of Artificial Intelligence
  Abstract: This paper attempts to showcase the benefits and merits of using artificial intelligence techniques in transportation applications. The example we use in this paper is modeling of a car-following trajectory data and comparing the machine learning approach to regression analysis. For the machine learning approach, we use Neuro-Fuzzy Actor-Critic Reinforcement Learning (NFACRL). We train the NFACRL network using vehicle trajectory data extracted from the Naturalistic Car Driving Study (NCDS) databases provided by the Virginia Tech Transportation Institute (VTTI). Our results show that both the machine learning and regression analysis could predict the upcoming acceleration value with a very high R2 value (more than 0.98). However, only the machine learning approach could reproduce the vehicle trajectory, while the regression analysis would ultimately lead to an erroneous model.
  Authors: Abbas, Montasir M.; Chong, Linsen
  Authors: Abbas, Montasir M.; Chong, Linsen
  Year: 2013
  Document Type: Paper
  Subject: Administration and Management; Data and Information Technology
  Session: 609
  Paper Number: 13-4712
• Shortest Paths in Stochastic Time-Dependent Networks with Link Travel Time Correlation
  Abstract: This paper develops a simple robust framework for the problem of finding the least expected travel time route from any node to any given destination in a stochastic and time-dependent network. We consider both spatial and temporal link travel time correlations in the proposed solution based on a dynamic programming approach. In particular, the spatial correlation is represented by a Markovian property of the link states where each link is assumed to experience congested or uncongested conditions. The temporal correlation is manifested through the time-dependent expected link travel time given the condition of the link traversed. The framework enables a route guidance system where at any decision node within a network, one can make a decision based on current traffic information about which node to take next to achieve the shortest expected travel time to the destination. Numerical examples are presented to illustrate the computational steps involved in the framework of making route choice decisions and to demonstrate the effectiveness of the proposed solution.
  Authors: Dong, Wei; Vu, Hai; Nazarathy, Yoni; Vo, Quoc Bao; Li, Minyi; Hoogendoorn, Serge
  Authors: Dong, Wei; Vu, Hai; Nazarathy, Yoni; Vo, Quoc Bao; Li, Minyi; Hoogendoorn, Serge
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology
  Session: 360
  Paper Number: 13-4872
• Future Mobility Survey: Experience in Developing a Smart-Phone-Based Travel Survey in Singapore
  Abstract: The Future Mobility Survey (FMS) is a smartphone-based prompted-recall travel survey that aims to support data collection initiatives for transport modeling purposes. This paper details the considerations that have gone into its development, including the smartphone apps for iPhone and Android platforms, the online activity diary and user interface, and the background intelligence for processing collected data into activity locations and travel traces. We discuss the various trade-offs regarding user comprehension, resource use, and participant burden, including findings from usability tests and a pilot study. We find that close attention should be paid to the simplicity of the user interaction, determinations of activity locations (such as the positive/false negative trade-off in their automatic classification), and the clarity of interactions in the activity diary. The FMS system design and implementation provides pragmatic, useful insights into the development of similar platforms and approaches for travel/activity surveys.
  Authors: Cottrill, Caitlin D.; Pereira, Francisco C.; Zhao, Fang;