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Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment

Author

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  • Xiaoyuan Wang

    (College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
    School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Junyan Han

    (College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
    Shandong Intelligent Green Manufacturing Technology and Equipment Collaborative Innovation Center, Qingdao 266000, China)

  • Chenglin Bai

    (School of Physics Science and Information Engineering, Liaocheng University, Liaocheng 252000, China)

  • Huili Shi

    (College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
    School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

  • Jinglei Zhang

    (Shandong Intelligent Green Manufacturing Technology and Equipment Collaborative Innovation Center, Qingdao 266000, China)

  • Gang Wang

    (College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
    School of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China)

Abstract

With the application of vehicles to everything (V2X) technologies, drivers can obtain massive traffic information and adjust their car-following behavior according to the information. The macro-characteristics of traffic flow are essentially the overall expression of the micro-behavior of drivers. There are some shortcomings in the previous researches on traffic flow in the V2X environment, which result in difficulties to employ the related models or methods in exploring the characteristics of traffic flow affected by the information of generalized preceding vehicles (GPV). Aiming at this, a simulation framework based on the car-following model and the cellular automata (CA) is proposed in this work, then the traffic flow affected by the information of GPV is simulated and analyzed utilizing this framework. The research results suggest that the traffic flow, which is affected by the information of GPV in the V2X environment, would operate with a higher value of velocity, volume as well as jamming density and can maintain the free flow state with a much higher density of vehicles. The simulation framework constructed in this work can provide a reference for further research on the characteristics of traffic flow affected by various information in the V2X environment.

Suggested Citation

  • Xiaoyuan Wang & Junyan Han & Chenglin Bai & Huili Shi & Jinglei Zhang & Gang Wang, 2021. "Research on the Impacts of Generalized Preceding Vehicle Information on Traffic Flow in V2X Environment," Future Internet, MDPI, vol. 13(4), pages 1-17, March.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:4:p:88-:d:526864
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    References listed on IDEAS

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    Cited by:

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    2. Junyan Han & Xiaoyuan Wang & Huili Shi & Bin Wang & Gang Wang & Longfei Chen & Quanzheng Wang, 2022. "Research on the Impacts of Vehicle Type on Car-Following Behavior, Fuel Consumption and Exhaust Emission in the V2X Environment," Sustainability, MDPI, vol. 14(22), pages 1-15, November.
    3. Pei, Yulong & Pan, Sheng & Wen, Yuhang, 2024. "Analysis of roadway capacity for heterogeneous traffic flows considering the degree of trust of drivers of HVs in CAVs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).

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