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Modeling AVs & RVs’ car-following behavior by considering impacts of multiple surrounding vehicles and driving characteristics

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  • Zong, Fang
  • Wang, Meng
  • Tang, Jinjun
  • Zeng, Meng

Abstract

This paper proposes a mixed-vehicles car-following model based on FVAD (Full Velocity and Acceleration Difference) model to describe the microscopic car-following behavior of RVs (Regular Vehicles) and AVs (Autonomous Vehicles). The model involves the velocity of multiple front vehicles and a rear vehicle as well as the velocity difference, acceleration difference and headway between each front vehicle and the host vehicle. As for AV’s car-following model we introduced the molecular dynamic theory to quantitatively express the influence of multiple front vehicles on the host vehicle. The velocity of multiple front vehicles and headway between each of them and the host vehicle are used to express the influence. Besides, we consider drivers’ car-following styles in constructing the RV model. The stability analysis results indicate that the stability of traffic flow under the proposed model is not easily affected by the change in velocity, and is better than FVAD model. According to the data collected from the car-following field test mixed with AVs and RVs, we obtain the optimal value of the parameters in the model, and examine the fitting accuracy with a numerical simulation. The results indicate that compared with FVAD model, the MME (Mean Maximum Error) and ME (Mean Error) of RV model is reduced by 39.50% and 13.12%, respectively, and the accuracy is improved by 14.48%. The acceleration strategy controlled by the AV model is smoother than by the ACC (Adaptive Cruise Control) model. With effective car-following behavior control, it is helpful to improve the operation efficiency of AVs and enhance the stability of traffic flow. Additionally, the model can be utilized for platoon control in the case of RVs’ and AVs’ heterogeneous flow. This model can also serve as a tool to simulate car-following behavior, which is beneficial for road traffic management and infrastructure layout in AV and RV mixed traffic environment.

Suggested Citation

  • Zong, Fang & Wang, Meng & Tang, Jinjun & Zeng, Meng, 2022. "Modeling AVs & RVs’ car-following behavior by considering impacts of multiple surrounding vehicles and driving characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    • Handle: RePEc:eee:phsmap:v:589:y:2022:i:c:s0378437121008785
    DOI: 10.1016/j.physa.2021.126625
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    References listed on IDEAS

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    Cited by:

    1. Li, Huamin & Jin, Shiyu, 2024. "Intelligent vehicle car-following model based on cyber physical system and its simulation under mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    2. Qin, Yanyan & Luo, Qinzhong & Xiao, Tengfei & He, Zhengbing, 2024. "Modeling the mixed traffic capacity of minor roads at a priority intersection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    3. 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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