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A car-following theory for multiphase vehicular traffic flow

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  • Zhang, H.M.
  • Kim, T.

Abstract

We present in this paper a new car-following theory that can reproduce both the so-called capacity drop and traffic hysteresis, two prominent features of multiphase vehicular traffic flow. This is achieved through the introduction of a single variable, gap-time, that depends on both vehicle gap-distance and traffic phase. By specifying different functional forms of gap-time, one can obtain not only brand new theories but also some of the well-known old car-following theories, which is demonstrated in this paper through both theoretical analysis and numerical simulation.

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  • Zhang, H.M. & Kim, T., 2005. "A car-following theory for multiphase vehicular traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 39(5), pages 385-399, June.
    • Handle: RePEc:eee:transb:v:39:y:2005:i:5:p:385-399
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    References listed on IDEAS

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    Cited by:

    1. Yaron Hollander & Ronghui Liu, 2008. "The principles of calibrating traffic microsimulation models," Transportation, Springer, vol. 35(3), pages 347-362, May.
    2. Siqueira, Adriano F. & Peixoto, Carlos J.T. & Wu, Chen & Qian, Wei-Liang, 2016. "Effect of stochastic transition in the fundamental diagram of traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 1-13.
    3. Bai, Lu & Wong, S.C. & Xu, Pengpeng & Chow, Andy H.F. & Lam, William H.K., 2021. "Calibration of stochastic link-based fundamental diagram with explicit consideration of speed heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 524-539.
    4. Kai Yuan & Victor L. Knoop & Serge P. Hoogendoorn, 2017. "A Microscopic Investigation Into the Capacity Drop: Impacts of Longitudinal Behavior on the Queue Discharge Rate," Transportation Science, INFORMS, vol. 51(3), pages 852-862, August.
    5. Jiang, Rui & Hu, Mao-Bin & Zhang, H.M. & Gao, Zi-You & Jia, Bin & Wu, Qing-Song, 2015. "On some experimental features of car-following behavior and how to model them," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 338-354.
    6. Zhang, Jin & Qu, Xiaobo & Wang, Shuaian, 2018. "Reproducible generation of experimental data sample for calibrating traffic flow fundamental diagram," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 41-52.
    7. Jabari, Saif Eddin & Zheng, Jianfeng & Liu, Henry X., 2014. "A probabilistic stationary speed–density relation based on Newell’s simplified car-following model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 205-223.
    8. Wang, Xiao & Jiang, Rui & Li, Li & Lin, Yi-Lun & Wang, Fei-Yue, 2019. "Long memory is important: A test study on deep-learning based car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 786-795.
    9. Hofleitner, Aude & Herring, Ryan & Bayen, Alexandre, 2012. "Arterial travel time forecast with streaming data: A hybrid approach of flow modeling and machine learning," Transportation Research Part B: Methodological, Elsevier, vol. 46(9), pages 1097-1122.
    10. Yeo, Hwasoo, 2008. "Asymmetric Microscopic Driving Behavior Theory," University of California Transportation Center, Working Papers qt1tn1m968, University of California Transportation Center.
    11. Qu, Xiaobo & Zhang, Jin & Wang, Shuaian, 2017. "On the stochastic fundamental diagram for freeway traffic: Model development, analytical properties, validation, and extensive applications," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 256-271.
    12. Koutsopoulos, Haris N. & Farah, Haneen, 2012. "Latent class model for car following behavior," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 563-578.
    13. Zhang, Qinglong & Liu, Shuzhi, 2023. "The Riemann problem and a Godunov-type scheme for a traffic flow model on two lanes with two velocities," Applied Mathematics and Computation, Elsevier, vol. 436(C).
    14. Chen, Danjue & Laval, Jorge A. & Ahn, Soyoung & Zheng, Zuduo, 2012. "Microscopic traffic hysteresis in traffic oscillations: A behavioral perspective," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1440-1453.
    15. Yibing Wang & Long Wang & Xianghua Yu & Jingqiu Guo, 2023. "Capacity Drop at Freeway Ramp Merges with Its Replication in Macroscopic and Microscopic Traffic Simulations: A Tutorial Report," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
    16. He, Shuyan & Guan, Wei & Song, Liying, 2010. "Explaining traffic patterns at on-ramp vicinity by a driver perception model in the framework of three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(4), pages 825-836.
    17. Chen, Danjue & Ahn, Soyoung & Laval, Jorge & Zheng, Zuduo, 2014. "On the periodicity of traffic oscillations and capacity drop: The role of driver characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 117-136.
    18. Zhao, Yongxiang & Zhang, H.M., 2017. "A unified follow-the-leader model for vehicle, bicycle and pedestrian traffic," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 315-327.
    19. Saifuzzaman, Mohammad & Zheng, Zuduo & Haque, Md. Mazharul & Washington, Simon, 2017. "Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 523-538.

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