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Modeling the heterogeneous traffic flow considering mean expected velocity field and effect of two-lane communication under connected environment

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  • Wang, Shutong
  • Zhu, Wen-Xing

Abstract

With the increasing popularity of the autonomous vehicles, heterogeneous traffic flow of autonomous vehicles (AVs) and human-driving vehicles (HDVs) will exist for long time. Based on single-lane mean expected velocity field model (MEV model), an improved two-lane heterogeneous car-following model (MEVTC model) is proposed which considers the mean expected velocity field of main lane and mean velocity field of adjacent lane in a connected environment. The strength factor of two fields are key parameters. Linear and nonlinear methods are used to reveal the basic characteristics of traffic flow under the new model. Theoretical results show that greater parameters mean larger stability regions. The MEVTC model is verified by numerical simulation, the results show that comparing with MEV model, MEVTC model can reduce the headway fluctuation by 11.2% and increase the traffic flow by 4.2%. With increased strength factor of two fields, the traffic flow becomes more stable However, the influence of the adjacent lane field on vehicle driving is dramatically smaller than main lane field. In addition, the higher penetration rate of the AVs is also good for the stability of traffic flow.

Suggested Citation

  • Wang, Shutong & Zhu, Wen-Xing, 2022. "Modeling the heterogeneous traffic flow considering mean expected velocity field and effect of two-lane communication under connected environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    • Handle: RePEc:eee:phsmap:v:607:y:2022:i:c:s0378437122007609
    DOI: 10.1016/j.physa.2022.128202
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