2013 Session: 725

• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• 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
• Predicting Road Casualties in Flanders in Relation to an Aging Population: Combining Decomposition and Disaggregation
  Abstract: This paper describes an approach to predict casualty rates in the Flanders region of Belgium. The objective of the paper is to demonstrate the strength of the proposed approach that combines the decomposition method with a disaggregate analysis as a prediction approach to study road safety problems. The prediction for the Flanders region will hereby serve as an illustration for this approach. The evolution of the number of casualties is explained by its components exposure and risk, where exposure is further decomposed into population numbers and the travel patterns of its individuals. Upon the decomposition a disaggregate approach is followed to take into account the various differences in exposure and risk that exist between distinct subgroups.A reduction of the number of casualties with 57% is found in 2020 compared to 2001. Our approach however also allows to determine the relative contribution of each component to the casualty rate. Because of the different trends in population, exposure and risk, casualty numbers evolve differently for different groups. Therefore their share in the total traffic casualties will change and new target groups for road safety policy emerge. In Flanders older women will be such new target group since it will become one of the most sizeable casualty groups.
  Authors: Van Hout, Kurt; Brijs, Tom; Daniels, Stijn; Hermans, Elke; Wets, Geert
  Authors: Van Hout, Kurt; Brijs, Tom; Daniels, Stijn; Hermans, Elke; Wets, Geert
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-5302
• Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies
  Abstract:

  Crash-prone drivers should be effectively targeted for various safety education and regulation programs because their over-involvement in crashes presents a big adverse effect on highway safety. By analyzing seven-years of crash data from Louisiana, this paper investigates crash-prone drivers’ characteristics and estimates their risk to have crashes in the seventh year based on these drivers' crash history of the past six years. The analysis results show that quite a few drivers repeatedly had crashes; seven drivers had 13 crashes in seven years; and the maximum number of crashes occurring in a single year to a single driver is eight. Actually, the 5% of drivers who had multiple crashes were responsible for 35% of the crashes that occurred in the seven years in Louisiana. Crash injury rate is also higher for drivers with multiple crashes. The probability of having crash(es) in any given year is closely related to a driver’s crash history; less than 4% for drivers with no crash in the previous six years; and slightly higher than 30% for drivers with nine or more crashes in the previous six years. There are variations in drivers’ age, gender, crash contribution factors, and type of crashes by the number of crashes. Based on the results, several suggestions are made on how to improve roadway safety through reducing crashes committed by drivers with much higher crash risk as identified by the analysis.

  Authors: Sun, Xiaoduan; Das, Subasish; Rasel, S.K.; Wang, Fan
  Authors: Sun, Xiaoduan; Das, Subasish; Rasel, S.K.; Wang, Fan
  Year: 2013
  Document Type: Paper
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3945
• Joint Analysis of Injury Severity of Drivers in Two-Vehicle Crashes Accommodating Seat Belt Use Endogeneity
  Authors: Paleti, Rajesh
  Authors: Paleti, Rajesh
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3845
• Generalized Nonlinear Models for Rear-End Crash Risk Analysis
  Authors: Lao, Yunteng
  Authors: Lao, Yunteng
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3903
• Crash Databases in Australasia, European Union, and United States: Review and Prospects for Improvement
  Authors: Montella, Alfonso
  Authors: Montella, Alfonso
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4219
• Some Insights into Roadway Geometric Effects on Interstate Crash Occurrence from a Crash Typology Perspective
  Authors: Ulfarsson, Gudmundur
  Authors: Ulfarsson, Gudmundur
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4344
• Automated Intersection Safety Evaluation Using Linear Referencing System Methods
  Authors: Yang, Fan
  Authors: Yang, Fan
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4566
• Examining Heterogeneity of Driver Behavior Using Temporal and Spatial Factors
  Authors: Ellison, Adrian
  Authors: Ellison, Adrian
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4541
• Investigating the Characteristics of Secondary Crashes on Freeways
  Authors: Yang, Hong
  Keywords: Secondary Crash; Traffic Incident; Sensor Data; Incident Management; Highway Operation; Freeway
  Authors: Yang, Hong
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4866
• The Magnitude of the Regression to the Mean Effect in Traffic Crashes
  Authors: De Pauw, Ellen
  Authors: De Pauw, Ellen
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3772
• Fully Bayesian Before-After Evaluation of Traffic Safety Improvements in the City of Edmonton, Canada
  Authors: Li, Simon
  Authors: Li, Simon
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4869
• Identifying Precrash Factors Between Cars and Trucks on Interstate Highways: Mixed Logit Model Approach
  Authors: Romo, Alicia
  Authors: Romo, Alicia
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3149
• Evolutionary Game Theoretic Approach to Rear-Ending Events on a Congested Freeway
  Authors: Chatterjee, Indrajit
  Keywords: poster presentation; poster design; poster template
  Authors: Chatterjee, Indrajit
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3326
• Analysis of Aggregate Crash Data in the United States for 1967-2010
  Authors: Borsos, Attila
  Authors: Borsos, Attila
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3947
• Traffic Indicators and Accidents: Case of Motorway Network in the South of France
  Authors: Aron, Maurice
  Authors: Aron, Maurice
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4638
• Development of a Geographic Information System for SafetyAnalyst for Location Selection and Output Visualization
  Authors: Alluri, Priyanka
  Authors: Alluri, Priyanka
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3969
• Screening Naturalistic Driving Study Data
  Authors: Wu, Kun-Feng
  Authors: Wu, Kun-Feng
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4293
• Real-Time Identification of Crash-Prone Traffic Conditions Under Different Weather on Freeways
  Authors: Xu, Chengcheng
  Authors: Xu, Chengcheng
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-4996
• Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies
  Authors: Sun, Xiaoduan
  Authors: Sun, Xiaoduan
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3945
• Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies
  Authors: Das, Subasish
  Authors: Das, Subasish
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Data and Information Technology; Safety and Human Factors
  Session: 725
  Paper Number: 13-3945