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Modeling and analyses for an extended car-following model accounting for drivers’ situation awareness from cyber physical perspective

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  • Chen, Dong
  • Sun, Dihua
  • Zhao, Min
  • Zhou, Tong
  • Cheng, Senlin

Abstract

In fact, driving process is a typical cyber physical process which couples tightly the cyber factor of traffic information with the physical components of the vehicles. Meanwhile, the drivers have situation awareness in driving process, which is not only ascribed to the current traffic states, but also extrapolates the changing trend. In this paper, an extended car-following model is proposed to account for drivers’ situation awareness. The stability criterion of the proposed model is derived via linear stability analysis. The results show that the stable region of proposed model will be enlarged on the phase diagram compared with previous models. By employing the reductive perturbation method, the modified Korteweg de Vries (mKdV) equation is obtained. The kink–antikink soliton of mKdV equation reveals theoretically the evolution of traffic jams. Numerical simulations are conducted to verify the analytical results. Two typical traffic Scenarios are investigated. The simulation results demonstrate that drivers’ situation awareness plays a key role in traffic flow oscillations and the congestion transition.

Suggested Citation

  • Chen, Dong & Sun, Dihua & Zhao, Min & Zhou, Tong & Cheng, Senlin, 2018. "Modeling and analyses for an extended car-following model accounting for drivers’ situation awareness from cyber physical perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 52-68.
    • Handle: RePEc:eee:phsmap:v:501:y:2018:i:c:p:52-68
    DOI: 10.1016/j.physa.2018.02.125
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    References listed on IDEAS

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    Cited by:

    1. Hu, Yanmei & Ma, Tianshan & Chen, Jianzhong, 2021. "Multi-anticipative bi-directional visual field traffic flow models in the connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    2. Zhou, Tong & Chen, Dong & Zheng, Linjiang & Liu, Weining & He, Yuchu & Liu, Zhongcheng, 2018. "Feedback-based control for coupled map car-following model with time delays on basis of linear discrete-time system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 174-185.
    3. Li, Chao & Zhao, Xiaomei & Xie, Dongfan, 2022. "Steady-state performance and dynamic performance of heterogeneous platoons under a connected environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 599(C).
    4. Chen, Jin & Sun, Dihua & Li, Yang & Zhao, Min & Liu, Weining & Jin, Shuang, 2021. "Human–machine cooperative scheme for car-following control of the connected and automated vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).

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