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An extended car-following model considering driver’s desire for smooth driving on the curved road

Author

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  • Sun, Yuqing
  • Ge, Hongxia
  • Cheng, Rongjun

Abstract

In real traffic, many driver’s desire to lower the fuel consumption by driving smoothly. In this paper, an extended car-following model considering the driver’s desire for smooth driving on a curved road is proposed. The desire for smooth driving can be considered as a control signal including the velocity difference between the steady and history velocity. The stability conditions are obtained by the control theory, and the modified Korteweg–de Vries (mKdV) equation is derived via the non-linear analysis method. The numerical simulations are carried out to analyze the control signal, the friction coefficient and radius of curved road effects on traffic flow. The results show that the control signal has a positive effect on improving traffic flow stability, while the stability decreases with the increase of the two other parameters.

Suggested Citation

  • Sun, Yuqing & Ge, Hongxia & Cheng, Rongjun, 2019. "An extended car-following model considering driver’s desire for smooth driving on the curved road," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    • Handle: RePEc:eee:phsmap:v:527:y:2019:i:c:s0378437119308301
    DOI: 10.1016/j.physa.2019.121426
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    Citations

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    Cited by:

    1. Zhang, Xiangzhou & Shi, Zhongke & Yang, Qiaoli & An, Xiaodong, 2024. "Impacts of visuo-spatial working memory on the dynamic performance and safety of car-following behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    2. 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).
    3. Kang, Chengjun & Qian, Yongsheng & Zeng, Junwei & Wei, Xuting & Zhang, Futao, 2024. "Analysis of stability, energy consumption and CO2 emissions in novel discrete-time car-following model with time delay under V2V environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    4. Zhang, Geng & Yin, Le & Pan, Dong-Bo & Zhang, Yu & Cui, Bo-Yuan & Jiang, Shan, 2020. "Research on multiple vehicles’ continuous self-delayed velocities on traffic flow with vehicle-to-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    5. Junyan Han & Xiaoyuan Wang & Gang Wang, 2022. "Modeling the Car-Following Behavior with Consideration of Driver, Vehicle, and Environment Factors: A Historical Review," Sustainability, MDPI, vol. 14(13), pages 1-27, July.
    6. Cui, Bo-Yuan & Zhang, Geng & Ma, Qing-Lu, 2021. "A stable velocity control strategy for a discrete-time car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 571(C).
    7. Chen, Jin & Sun, Dihua & Zhao, Min & Li, Yang & Liu, Zhongcheng, 2021. "DCFS-based deep learning supervisory control for modeling lane keeping of expert drivers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).

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