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A modified full velocity difference model with the consideration of velocity deviation

Author

Listed:
  • Jie Zhou

    (College of Automation, Northwestern Polytechnical University, Xi’an, Shanxi 710072, P. R. China)

  • Zhong-Ke Shi

    (College of Automation, Northwestern Polytechnical University, Xi’an, Shanxi 710072, P. R. China)

Abstract

In this paper, a modified full velocity difference model (FVDM) based on car-following theory is proposed with the consideration of velocity deviation which represents the inexact judgement of velocity. The stability condition is obtained by the use of linear stability analysis. It is shown that the stability of traffic flow varies with the deviation extent of velocity. The Burgers, Korteweg-de Vries (KdV) and modified K-dV (MKdV) equations are derived to describe the triangular shock waves, soliton waves and kink–antikink waves in the stable, metastable and unstable region, respectively. The numerical simulations show a good agreement with the analytical results, such as density wave, hysteresis loop, acceleration, deceleration and so on. The results show that traffic congestion can be suppressed by taking the positive effect of velocity deviation into account. By taking the positive effect of high estimate of velocity into account, the unrealistic high deceleration and negative velocity which occur in FVDM will be eliminated in the proposed model.

Suggested Citation

  • Jie Zhou & Zhong-Ke Shi, 2016. "A modified full velocity difference model with the consideration of velocity deviation," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(06), pages 1-19, June.
    • Handle: RePEc:wsi:ijmpcx:v:27:y:2016:i:06:n:s0129183116500698
    DOI: 10.1142/S0129183116500698
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    Cited by:

    1. Sun, Lu & Jafaripournimchahi, Ammar & Hu, Wusheng, 2020. "A forward-looking anticipative viscous high-order continuum model considering two leading vehicles for traffic flow through wireless V2X communication in autonomous and connected vehicle environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).
    2. Pan, Weixiu & Zhang, Jing & Tian, Junfang & Cui, Fengying & Wang, Tao, 2023. "Analysis of car–following behaviors based on data–driven and theory–driven car–following models: Heterogeneity and asymmetry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).

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