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A car-following dynamic model with headway memory and evolution trend

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  • Cao, Bao-gui

Abstract

Integrating headway evolution information into the existing memory car-following model, a new car-following dynamic model with headway memory and evolution trend is proposed in this paper. The objective of this research is to investigate the impacts and improvements of a combined consideration of headway memory and evolution trend on micro driving behaviors and the stability of traffic flow. The neutral stability condition of the proposed model is obtained by means of linear stability theory. The model is investigated in detail by numerical comparison under two typical cases, where Case I is the starting process and Case II is the development process of a small perturbation. Numerical results show that driver’s headway memory and evolution trend have opposite impacts on the stability of traffic flow, which means the extended car-following model can compensate for unavoidable sensory memory delay for the reliability of headway perception and effectively suppress traffic congestion since the headway evolution trend effect is taken into account.

Suggested Citation

  • Cao, Bao-gui, 2020. "A car-following dynamic model with headway memory and evolution trend," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    • Handle: RePEc:eee:phsmap:v:539:y:2020:i:c:s0378437119316474
    DOI: 10.1016/j.physa.2019.122903
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    Citations

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    Cited by:

    1. 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).
    2. 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).
    3. Wang, Xiaoning & Liu, Minzhuang & Ci, Yusheng & Wu, Lina, 2022. "Effect of front two adjacent vehicles’ velocity information on car-following model construction and stability analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    4. Yin, Yu-Hang & Lü, Xing & Jiang, Rui & Jia, Bin & Gao, Ziyou, 2024. "Kinetic analysis and numerical tests of an adaptive car-following model for real-time traffic in ITS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    5. Junyan Han & Jinglei Zhang & Xiaoyuan Wang & Yaqi Liu & Quanzheng Wang & Fusheng Zhong, 2020. "An Extended Car-Following Model Considering Generalized Preceding Vehicles in V2X Environment," Future Internet, MDPI, vol. 12(12), pages 1-15, November.
    6. Yi, Ziwei & Lu, Wenqi & Qu, Xu & Gan, Jing & Li, Linheng & Ran, Bin, 2022. "A bidirectional car-following model considering distance balance between adjacent vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    7. Shuaiyang Jiao & Shengrui Zhang & Bei Zhou & Zixuan Zhang & Liyuan Xue, 2020. "An Extended Car-Following Model Considering the Drivers’ Characteristics under a V2V Communication Environment," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    8. Ma, Guangyi & Ma, Minghui & Liang, Shidong & Wang, Yansong & Guo, Hui, 2021. "Nonlinear analysis of the car-following model considering headway changes with memory and backward looking effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    9. Zhiyong Zhang & Wu Tang & Wenming Feng & Zhen Liu & Caixia Huang, 2024. "An Extended Car-Following Model Considering Lateral Gap and Optimal Velocity of the Preceding Vehicle," Sustainability, MDPI, vol. 16(14), pages 1-20, July.

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