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Self-driven particle model for mixed traffic and other disordered flows

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  • Kanagaraj, Venkatesan
  • Treiber, Martin

Abstract

Vehicles in developing countries have widely varying dimensions and speeds, and drivers tend to not follow lane discipline. In this flow state called “mixed traffic”, the interactions between drivers and the resulting maneuvers resemble more that of general disordered self-driven particle systems than that of the orderly lane-based traffic flow of industrialized countries. We propose a general multi particle model for such self-driven “high-speed particles” and show that it reproduces the observed characteristics of mixed traffic. The main idea is to generalize a conventional acceleration-based car-following model to a two-dimensional force field. For in-line following, the model reverts to the underlying car-following model, for very slow speeds, it reverts to an anisotropic social-force model for pedestrians. With additional floor fields at the position of lane markings, the model reverts to an integrated car-following and lane-changing model with continuous lateral dynamics including cooperative aspects such as zip merging. With an adaptive cruise control (ACC) system as underlying car-following model, it becomes a controller for the acceleration and steering of autonomous vehicles in mixed or lane-based traffic.

Suggested Citation

  • Kanagaraj, Venkatesan & Treiber, Martin, 2018. "Self-driven particle model for mixed traffic and other disordered flows," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1-11.
  • Handle: RePEc:eee:phsmap:v:509:y:2018:i:c:p:1-11
    DOI: 10.1016/j.physa.2018.05.086
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    References listed on IDEAS

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    1. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    2. Gipps, P. G., 1986. "A model for the structure of lane-changing decisions," Transportation Research Part B: Methodological, Elsevier, vol. 20(5), pages 403-414, October.
    3. Gunay, Banihan, 2007. "Car following theory with lateral discomfort," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 722-735, August.
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    Citations

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    Cited by:

    1. Maiti, Nandan & Chilukuri, Bhargava Rama, 2023. "Does anisotropy hold in mixed traffic conditions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    2. Nagahama, Akihito & Wada, Takahiro & Yanagisawa, Daichi & Nishinari, Katsuhiro, 2021. "Detection of leader–follower combinations frequently observed in mixed traffic with weak lane-discipline," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    3. Li, Yixin & Ni, Ying & Sun, Jian & Ma, Zian, 2020. "Modeling the illegal lane-changing behavior of bicycles on road segments: Considering lane-changing categories and bicycle heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    4. Hou, Xianlei & Zhang, Rui & Yang, Minghui & Cheng, Shida, 2024. "Modeling the lane-changing behavior of non-motorized vehicles on road segments via social force model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    5. Maosheng Li & Qian Luo & Jing Fan & Qingyan Ning, 2023. "Impact Analysis of Smart Road Stud on Driving Behavior and Traffic Flow in Two-Lane Two-Way Highway," Sustainability, MDPI, vol. 15(15), pages 1-20, July.
    6. Chengju Song & Hongfei Jia, 2022. "Multi-State Car-Following Behavior Simulation in a Mixed Traffic Flow for ICVs and MDVs," Sustainability, MDPI, vol. 14(20), pages 1-12, October.
    7. Sun, Qipeng & Cheng, Qianqian & Wang, Yongjie & Li, Tao & Ma, Fei & Yao, Zhigang, 2022. "Zip-merging behavior at Y-intersection based on intelligent travel points," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).

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