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Behavior-based analysis of freeway car-truck interactions and related mitigation strategies

Author

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  • Peeta, Srinivas
  • Zhang, Pengcheng
  • Zhou, Weimin

Abstract

Freight trucks are an important component of the nation's highway traffic. Due to their physical and operational characteristics, they can significantly impact traffic system performance, safety, and the travel experience of non-truck drivers. Methodological gaps exist in the literature on modeling car-truck interactions that do not result in crashes, especially those resulting from non-truck driver behavior. This paper focuses on the modeling of the behavior of non-truck drivers in the vicinity of trucks to capture these interactions. This is done by quantifying a time-dependent "discomfort level" for every non-truck driver interacting with trucks in the ambient traffic stream. The driver socioeconomic characteristics and situational factors that affect this discomfort are identified through a stated preference survey of non-truck drivers and a preliminary analysis of the survey data using a discrete choice model. A fuzzy logic based approach is proposed to determine the en-route time-dependent non-truck driver discomfort level. This is used in conjunction with the car-following and lane-changing logics of a traditional traffic flow model to generate a truck-following model and a modified lane-changing model in the vicinity of trucks. An agent-based freeway segment traffic flow simulator is constructed using the extended microscopic flow modeling logic. It provides a simulation-based framework to analyze alternative strategies to mitigate car-truck interactions. Experiments are conducted to analyze the sensitivity of the discomfort level to the causal variables, and evaluate the effectiveness of alternative mitigation strategies.

Suggested Citation

  • Peeta, Srinivas & Zhang, Pengcheng & Zhou, Weimin, 2005. "Behavior-based analysis of freeway car-truck interactions and related mitigation strategies," Transportation Research Part B: Methodological, Elsevier, vol. 39(5), pages 417-451, June.
    • Handle: RePEc:eee:transb:v:39:y:2005:i:5:p:417-451
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    Cited by:

    1. Dewen Kong & Xiucheng Guo & Bo Yang & Dingxin Wu, 2016. "Analyzing the Impact of Trucks on Traffic Flow Based on an Improved Cellular Automaton Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-14, September.
    2. Junyan Han & Xiaoyuan Wang & Huili Shi & Bin Wang & Gang Wang & Longfei Chen & Quanzheng Wang, 2022. "Research on the Impacts of Vehicle Type on Car-Following Behavior, Fuel Consumption and Exhaust Emission in the V2X Environment," Sustainability, MDPI, vol. 14(22), pages 1-15, November.
    3. Yang, Da & Qiu, Xiaoping & Yu, Dan & Sun, Ruoxiao & Pu, Yun, 2015. "A cellular automata model for car–truck heterogeneous traffic flow considering the car–truck following combination effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 62-72.
    4. Yang, Da & Jin, Peter (Jing) & Pu, Yun & Ran, Bin, 2014. "Stability analysis of the mixed traffic flow of cars and trucks using heterogeneous optimal velocity car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 371-383.
    5. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    6. Pazour, Jennifer A. & Meller, Russell D. & Pohl, Letitia M., 2010. "A model to design a national high-speed rail network for freight distribution," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(3), pages 119-135, March.
    7. Liu, Lan & Zhu, Liling & Yang, Da, 2016. "Modeling and simulation of the car-truck heterogeneous traffic flow based on a nonlinear car-following model," Applied Mathematics and Computation, Elsevier, vol. 273(C), pages 706-717.
    8. Shanchuan Yu & Yu Chen & Lang Song & Zhaoze Xuan & Yi Li, 2023. "Modelling and Mitigating Secondary Crash Risk for Serial Tunnels on Freeway via Lighting-Related Microscopic Traffic Model with Inter-Lane Dependency," IJERPH, MDPI, vol. 20(4), pages 1-29, February.
    9. Li, Xin & Li, Xingang & Xiao, Yao & Jia, Bin, 2016. "Modeling mechanical restriction differences between car and heavy truck in two-lane cellular automata traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 49-62.
    10. Anderson, Jason R. & Ogden, Jeffrey D. & Cunningham, William A. & Schubert-Kabban, Christine, 2017. "An exploratory study of hours of service and its safety impact on motorists," Transport Policy, Elsevier, vol. 53(C), pages 161-174.

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