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Adapting a cellular automata model to describe heterogeneous traffic with human-driven, automated, and communicating automated vehicles

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  • Vranken, Tim
  • Sliwa, Benjamin
  • Wietfeld, Christian
  • Schreckenberg, Michael

Abstract

This paper introduces a cellular automaton design for single lane highway sections with a reduced time step length of 0.1 s. It is able to model automated and human vehicle agents in heterogeneous as well as homogeneous traffic. Furthermore, it allows agents to adopt different behaviour patterns depending on whether they follow automated or human vehicle agents. A distinction between communicating and non-communicating automated vehicles is also possible. Simulations showed that autonomous vehicles are expected to increase road capacity, reduce the frequency and lifetime of traffic jams, and improve traffic synchronisation. Homogeneous communicating automated vehicles traffic can increase the capacity up to about 480% compared to conventional traffic. Furthermore, potential problems with the human–robot interaction that could result in accidents were identified and removed.

Suggested Citation

  • Vranken, Tim & Sliwa, Benjamin & Wietfeld, Christian & Schreckenberg, Michael, 2021. "Adapting a cellular automata model to describe heterogeneous traffic with human-driven, automated, and communicating automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    • Handle: RePEc:eee:phsmap:v:570:y:2021:i:c:s0378437121000649
    DOI: 10.1016/j.physa.2021.125792
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    References listed on IDEAS

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    Cited by:

    1. Wang, Jinghui & Lv, Wei & Jiang, Yajuan & Qin, Shuangshuang & Li, Jiawei, 2021. "A multi-agent based cellular automata model for intersection traffic control simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    2. Lyu, Zelin & Hu, Xiaojian & Zhang, Fang & Liu, Tenghui & Cui, Zhiwei, 2022. "Heterogeneous traffic flow characteristics on the highway with a climbing lane under different truck percentages: The framework of Kerner’s three-phase traffic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 587(C).
    3. Zhang, Xiangzhou & Shi, Zhongke & Chen, Jianzhong & Ma, lijing, 2023. "A bi-directional visual angle car-following model considering collision sensitivity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    4. Jing, Dian & Yao, Enjian & Chen, Rongsheng, 2023. "Moving characteristics analysis of mixed traffic flow of CAVs and HVs around accident zones," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    5. Jiang, Yangsheng & Wang, Sichen & Yao, Zhihong & Zhao, Bin & Wang, Yi, 2021. "A cellular automata model for mixed traffic flow considering the driving behavior of connected automated vehicle platoons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    6. Vranken, Tim & Schreckenberg, Michael, 2022. "Modelling multi-lane heterogeneous traffic flow with human-driven, automated, and communicating automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).

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