2013 Session: 603

• Performance Benchmarking of Road Weather Information System Pavement Temperature Forecasts
  Abstract: This paper describes a study focusing on performance evaluation of RWIS pavement temperature forecasts. To identify the factors influencing the accuracy of forecasts, five research hypotheses were constructed that RWIS forecasting accuracy would be affected by climatic patterns (e.g., maritime, continental, and mixed), locational attributes (e.g., geography), seasonal variations (e.g., shoulder months vs. non-shoulder months), time of day (e.g., day vs. night), and forecast horizon. RWIS observations and forecasts data sets provided by four North American provincial transportation agencies were pre-processed and stratified by station, hour, and month, to test the hypotheses and quantify their effects by utilizing two performance metrics, namely mean absolute error (MAE) and percent of acceptable forecasts (PAF). The overall statistics showed that maritime climate group had the highest correspondence and those from mixed climate group had the lowest correspondence, both in terms of their MAEs and PAF. As for the locational attributes, it was found that the forecasting performance of maritime region near coastal areas was found to have a negative correlation with the distance from nearby large water body. It was also found that daytime forecasts were less accurate than the ones generated for night time. Furthermore, the accuracy of forecasts was found to deteriorate quickly as the forecasting horizon increases. Lastly, forecast errors were found to exhibit seasonal variations with forecasts for the shoulder/transitional months tending to be poorer than other months.
  Authors: Kwon, Tae-Jung; Fu, Liping; Perchanok, Max S.
  Authors: Kwon, Tae-Jung; Fu, Liping; Perchanok, Max S.
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-1764
• Test on Driving Behavior and Judgement of Appropriate Speed with Different Road Surfaces Conditions in Curve Sections
  Abstract: For safe driving, it is essential that the driver properly recognize road alignment, pavement markings and other traffic control devices. At the same time, road surface conditions vary with weather conditions. In snowy regions, the road surface during winter can be compacted-snow, dry or wet. Under the compacted-snow condition, drivers are not able to see the pavement markings, and on rural highways, control speed according to the linear curve is important for safe. In autumn 2011 and winter 2012, the authors conducted driving tests on driving behavior and selection speed under the dry and compacted-snow conditions in curve section of two-lane highway. Ten drivers participated in a test on a road section in service. An eyes measurement system with vehicle dynamics recorder was installed on a test vehicle that traveled both directions on a 10.5-km test section of two-lane highway in Eastern Hokkaido, Japan. Ten male drivers drove the test vehicle under free-flow condition. The test vehicle was traveling in various curves of test section. The driving behavior in the curve sections recorded using a vehicle dynamics recorder on the rear seat. It was found that the selection speed of driver in the curve section is lower for the compacted-snow condition than for the dry condition, and that the variation in lateral acceleration was lower for the compacted-snow condition than for the dry condition.
  Authors: Munehiro, Kazunori; Kageyama, Hiroyuki; Takahashi, Naoto; Ishida, Tateki; Asano, Motoki
  Authors: Munehiro, Kazunori; Kageyama, Hiroyuki; Takahashi, Naoto; Ishida, Tateki; Asano, Motoki
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-1633
• METEOSAFETY: Multiagent System to Support Automated Activation of Traffic Management Plans for Adverse Weather Situations
  Abstract: The dynamism of traffic flows implies the research and new technologies development within traffic management and control strategies to achieve the improvement of traffic flows and road safety. Artificial intelligence could support traffic entities and road operators to manage possible incidents on the road network, especially when the incidents are related to adverse weather conditions. In this case, the probability of road accidents is increased due to the difficulty of driving under bad weather conditions. Thus, when an incident occurs road operators must decide how to cope with it in order to improve traffic safety. In Meteosafety project, a new MultiAgent System (MAS) to support traffic management has been developed. MAS technology helps to deal with the specific characteristics of traffic domain. The proposed MAS is able to work in two ways: a) coordinately, where all the agents work to solve weather problems in large networks and b) locally, where if communications breakdown, a small groups of agents work together to inform road users about weather problems. MAS is based on a rule-based system. This system is able to produce meteorological alarms with a high level of quality by applying specific coherence and correlation rules. So, it improves the road operator confidence in the decisions taken by the expert system. Furthermore it supports road operators proposing the best actions to take when any adverse weather situations with influence in the traffic flow happens.
  Authors: Tomás-López, Vicente R.; Martínez, Juan José; Soriano, Francisco R.; Martínez, Javier
  Authors: Tomás-López, Vicente R.; Martínez, Juan José; Soriano, Francisco R.; Martínez, Javier
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-1980
• Transportation System Performance Under Inclement Winter Weather: Perspectives from Weather-Induced Multiple Hazard Situations and Traveler Information
  Abstract: This study investigated the impacts of weather-induced multiple hazard situations, such as a snow storm accompanies by a major car accident on a highway, on road network performance in urban areas. A dynamic traffic assignment model was built for the study area in Amherst, New York, using the mesoscopic dynamic traffic assignment simulation package DynusT. Various hazard scenarios were simulated, including single events such as a snow storm or a car accident only scenarios and the combination of them. Both network-wide analyses and link-based analyses were conducted to examine the impact of hazard situations on travel time. In addition, different traveler information mitigation strategies were also evaluated based on the weather-induced multiple hazard situation. The results indicate that weather-induced multiple hazard situation affects network performance more significantly than single events. As traveler information dissemination strategies are concerned, both the variable message signs (VMS) and the en-route guidance are effective in mitigating hazard impact. En-route guidance performs better from the system perspective and brings more travel time savings. In comparison, VMS are more beneficial to the vehicles that are subject to both inclement weather and weather-induced incidents. Based on the findings, practical implications were produced to help traffic operation agencies to select appropriate traveler information dissemination strategies and determine the best information coverage rate.
  Authors: Hu, Jinge; Wang, Qian; Sadek, Adel W.; Wang, Zhiyong
  Authors: Hu, Jinge; Wang, Qian; Sadek, Adel W.; Wang, Zhiyong
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-2000
• Impacts of Influential Factors on Vehicle-to-Vehicle Crash Frequency and Severity in Rainy Weather
  Abstract: This study combined vehicle to vehicle crash frequency and severity estimations to examine factor impacts on Wisconsin highway safety in rainy weather. Primary tasks for this study were conducted as follows. Due to data deficiency, real-time rainfall intensity, water film depth, stopping sight distance, deficiency of car-following distance, and vertical curve grade were estimated through available data sources and GIS analysis to capture rainy weather conditions at the crash location and time. For crash frequency, a negative binomial regression model was estimated while ordered logit and multinomial logit models were compared for crash severity estimation.In crash frequency estimation, average annual daily traffic per lane and the interaction between posted speed limit change and off-ramp existence were found to increase the likelihood of vehicle to vehicle crash occurrences under rainfall. However, more average monthly rainfall and a wider left shoulder width were identified as factors that decrease the likelihood of vehicle to vehicle crash occurrences. In crash severity estimation, higher speed limit, driver's lateral lane control, and no use of safety belt were found to increase the likelihood of severe crashes, especially fatal, incapacitating, and non-incapacitating crashes under rainfall in the multinomial logit model that outperformed the ordered logit model. As an exploratory data analysis, this study provide insight into potential strategies for rainy weather highway safety improvement. The following weather sensitive strategies could prove effective: education enhancement, road design, and ITS implementation for driver's safety awareness under rainfall.
  Authors: Jung, Soyoung; Jang, Kitae; Yoon, Yoonjin; Kang, Sanghyeok
  Authors: Jung, Soyoung; Jang, Kitae; Yoon, Yoonjin; Kang, Sanghyeok
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-3308
• Prediction of Coastal Flooding and Evacuation Demand Estimation Considering Climate Change
  Abstract: Climate change consequences such as sea level rise have put residents and transportation systems in the Tri-State coastal regions around New York at a risk for catastrophic flooding events, and it has become urgently needed to develop capabilities to predict the impact of such events. In this paper, we propose an approach to predict coastal flooding and analyze its impact on transportation systems and population in the region. In particular, the three-dimensional coastal ocean model FVCOM is coupled with a two-dimensional shallow water model to simulate hydrodynamic flooding with resolution desired to resolve traffic systems such as streets at an affordable expense. A hydrological method is also proposed to estimate flooding resulting from overland runoff. The hydrodynamic and hydrological methods are combined to determine the entire flooded region. On the basis of the predicted areas of flooding, the demand to be evacuated may be estimated. To demonstrate its capabilities and performance, the proposed approach is applied to flooding along Cape May coastlines in the Delaware Bay under projected sea level and storm conditions. Simulations indicate that sea level rise indeed leads to a substantial increase in the total flooded area. Transportation facilities and local population will be significantly impacted in this region as discussed in the results of the case study.
  Authors: Tang, Hansong; Chien, Steven I-Jy; Marouane, Temimi; Qu, Ke; Zhao, Liuhui; Blain, Cheryl Ann; Kraatz, Simon
  Authors: Tang, Hansong; Chien, Steven I-Jy; Marouane, Temimi; Qu, Ke; Zhao, Liuhui; Blain, Cheryl Ann; Kraatz, Simon
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-4729
• Impact of Inclement Winter Weather on Border Crossing Traffic: Findings and Implications from Niagara Frontier Border
  Abstract: This paper focuses on one type of critical infrastructure of transportation systems, i.e., international border crossings, and is intended to assess the impact of inclement winter weather such as snow on border crossing traffic volumes. One of the busiest bridge crossings of the Niagara Frontier border, the Peace Bridge, was chosen as the study case. The daily traffic volume data collected from year 2003 to 2009, combined with weather information in the same period, was used to quantify the impact of snow on border crossing traffic. As found from the regression analysis, the daily snowfall, the ground snow accumulation and the average wind speed are significant in discouraging both auto travels and truck trips, and thus reducing border crossing traffic. In terms of vehicle type, truck trips are more prone to snow effects than auto trips. The marginal volume reduction rates with respect to one-inch snowfall range from 2.4% to 3.0% for trucks, but 1.5% to 2.1% for autos. The findings and quantitative effects can be used by traffic operation agencies to estimate changes of border crossing performance under different snow conditions. Meanwhile, the output of these analyses can facilitate the selection of appropriate mitigation strategies.
  Authors: Wang, Qian; Hu, Jinge
  Authors: Wang, Qian; Hu, Jinge
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-5234
• Prediction of Typhoon Impact on Transportation Networks with Support Vector Regression
  Abstract: Typhoon (or Pacific tropical cyclones) is one of the major natural disasters in the world. Typhoons affect transportation network, cause serious delay, damage roads, decrease the reliability of infrastructure and threaten our lives. In order to avoid serious delay due to the unexpected damaged roads under typhoons, the prediction of typhoon impact on transportation networks is important to reduce the risk of lives. This research focuses on the prediction of typhoon impact on transportation networks with SVR. Support vector regression (SVR) has been used for regression problems and is capable of dealing with complex systems with small data. The input data in SVR model is the historical cumulative damaged roads and maximum cumulative precipitations under typhoons in the past years. The output data is the cumulative damaged roads in the target year. The calibrated model is then applied to predict possible damages and used to evaluate different traffic management strategies in a realistic simulation environment. The calibration results show that MAPE of SVR prediction model is 9.7%. Traffic strategies can be developed based on the prediction information and can significantly improve the network reliability.
  Authors: Hu, Ta-Yin; Ho, Wei-Ming
  Authors: Hu, Ta-Yin; Ho, Wei-Ming
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-2609
  Practice-Ready: Yes
• Test on Driving Behavior and Judgement of Appropriate Speed with Different Road Surfaces Conditions in Curve Sections
  Authors: Kageyama, Hiroyuki
  Authors: Kageyama, Hiroyuki
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-1633
• Performance Benchmarking of Road Weather Information System Pavement Temperature Forecasts
  Authors: Kwon, Tae-Jung
  Authors: Kwon, Tae-Jung
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-1764
• METEOSAFETY: Multiagent System to Support Automated Activation of Traffic Management Plans for Adverse Weather Situations
  Authors: Tomas-López, Vicente
  Authors: Tomas-López, Vicente
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-1980
• Impacts of Influential Factors on Vehicle-to-Vehicle Crash Frequency and Severity in Rainy Weather
  Authors: Jung, Soyoung
  Authors: Jung, Soyoung
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-3308
• Prediction of Coastal Flooding and Evacuation Demand Estimation Considering Climate Change
  Authors: Tang, Hansong
  Authors: Tang, Hansong
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-4729
• Impact of Inclement Winter Weather on Border Crossing Traffic: Findings and Implications from Niagara Frontier Border
  Authors: Wang, Qian
  Authors: Wang, Qian
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-5234
• Transportation System Performance Under Inclement Winter Weather: Perspectives from Weather-Induced Multiple Hazard Situations and Traveler Information
  Authors: Sadek, Adel
  Authors: Sadek, Adel
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-2000
• Implementation and Evaluation of Weather-Responsive Traffic Management Strategies: Insight from Different Networks
  Authors: Kim, Jiwon
  Authors: Kim, Jiwon
  Year: 2013
  Document Type: Presentation; Poster
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-5287
• Implementation and Evaluation of Weather-Responsive Traffic Management Strategies: Insight from Different Networks
  Abstract:

  The study presents the development and application of methodologies to support Weather Responsive Traffic Management (WRTM) strategies, building on Traffic Estimation and Prediction System (TrEPS) models. First, a systematic framework for implementing and evaluating WTRM strategies under severe weather conditions is developed, where activities for planning, preparing and deploying WRTM strategies are identified in three different time frames: long-term strategic planning, short-term tactical planning and real-time traffic management center (TMC) operations. Next, the evaluation of various strategies is demonstrated using locally calibrated network simulation-assignment model capabilities, and special-purpose key performance indicators (KPIs) are introduced. Three types of WRTM strategies: demand management, advisory and control VMS (variable message signs), and incident management VMS are applied to multiple major US cities, which include Chicago, Salt Lake City and New York’s Long Island. The analysis results illustrate benefits of WRTM under inclement weather conditions and emphasize the importance of incorporating a predictive capability into selecting and deploying WRTM strategies.

  Authors: Kim, Jiwon; Mahmassani, Hani S.; Alfelor, Roemer; Chen, Ying; Hou, Tian; Jiang, Lan; Saberi, Meead; Verbas, Ismail Omer; Zockaie Kheiraie, Ali
  Authors: Kim, Jiwon; Mahmassani, Hani S.; Alfelor, Roemer; Chen, Ying; Hou, Tian; Jiang, Lan; Saberi, Meead; Verbas, Ismail Omer; Zockaie Kheiraie, Ali
  Year: 2013
  Document Type: Paper
  Subject: Maintenance and Preservation; Operations and Traffic Management
  Session: 603
  Paper Number: 13-5287
  Practice-Ready: Yes