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Dynamic performance and safety analysis of car-following models considering collision sensitivity

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  • Jiao, Shuaiyang
  • Zhang, Shengrui
  • Zhou, Bei
  • Zhang, Lei
  • Xue, Liyuan

Abstract

Car-following behavior is strongly related to the dynamic performance and safety of vehicles, and these behaviors must be studied more comprehensively. This study first quantitatively analyzes the relationship between time to collision and car-following behavior, and then proposes the concept of collision sensitivity coefficient. Based on the full velocity difference model, we introduce the collision sensitivity coefficient into the car-following model to explore its effect on vehicle dynamic performance and safety from a different perspective. The stability of traffic flow is investigated using linear stability theory and obtain the neutral stability condition of the proposed model. Numerical simulation results show that the proposed model can improve the stability of traffic flow and successfully suppress traffic jams. The computation results using various safety evaluation indicators reveal that the proposed model not only has better dynamic performance than the full velocity difference model but also can effectively improve the safety of vehicles. We conclude that collision sensitivity substantially affects car-following behavior.

Suggested Citation

  • Jiao, Shuaiyang & Zhang, Shengrui & Zhou, Bei & Zhang, Lei & Xue, Liyuan, 2021. "Dynamic performance and safety analysis of car-following models considering collision sensitivity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    • Handle: RePEc:eee:phsmap:v:564:y:2021:i:c:s0378437120308025
    DOI: 10.1016/j.physa.2020.125504
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    References listed on IDEAS

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    Cited by:

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    2. Torkashvand, Mojtaba Bahrami & Aghayan, Iman & Qin, Xiao & Hadadi, Farhad, 2022. "An extended dynamic probabilistic risk approach based on a surrogate safety measure for rear-end collisions on two-lane roads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    3. Zhang, Xiangzhou & Shi, Zhongke & Yu, Shaowei & Ma, Lijing, 2023. "A new car-following model considering driver’s desired visual angle on sharp curves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    4. Wu, Zhibei & Sun, Jitao & Xu, Ruihua, 2021. "Consensus-based connected vehicles platoon control via impulsive control method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 580(C).
    5. Maosheng Li & Jing Fan & Jaeyoung Lee, 2023. "Modeling Car-Following Behavior with Different Acceptable Safety Levels," Sustainability, MDPI, vol. 15(7), pages 1-23, April.

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