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Traffic Flow State Analysis Considering Driver Response Time and V2V Communication Delay in Heterogeneous Traffic Environment

Author

Listed:
  • Shan Guan

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Chicheng Ma

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

  • Jianjun Wang

    (College of Transportation Engineering, Chang’an University, Xi’an 710064, China)

Abstract

In order to study the heterogeneous traffic environment generated by connected automated vehicles (CAVs) and human-driven vehicles (HDVs), the car-following model and basic graph model of the mixed traffic flows of connected automated vehicles and human-driven vehicles are constructed. Considering driver response time and the communication delay of the connected automated vehicles control system, the three-parameter variation law of traffic flow is summarized to solve the traffic congestion problem in heterogeneous traffic environments. Firstly, the probability of six scenarios in queues of cooperative adaptive cruise control (CACC) vehicles, adaptive cruise control (ACC) vehicles, and human-driven vehicles in heterogeneous traffic environments is analyzed. The car-following model is defined, and the parameters are calibrated, and then a fundamental diagram model of traffic flow balance is derived. On this basis, considering driver response time and the communication delay of the linear controller, a car-following model considering multi-party delay is updated and established, and the heterogeneous traffic flow analysis of the two types of delays in the model is carried out. Finally, the microscopic simulation environment is constructed based on SUMO 1.17.0 (Simulation of Urban Mobility) software. The results show that when the permeability (the proportion of connected automated vehicles in a traffic stream) exceeds 0.6, CAVs account for the main part in the heterogeneous traffic, which has a positive impact on the maximum flow and the optimal density and can effectively improve the maximum capacity of the road. The simulation results show that the updated car-following model is reasonable and accurate in dealing with driver response time and V2V communication delay.

Suggested Citation

  • Shan Guan & Chicheng Ma & Jianjun Wang, 2023. "Traffic Flow State Analysis Considering Driver Response Time and V2V Communication Delay in Heterogeneous Traffic Environment," Sustainability, MDPI, vol. 15(11), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:8459-:d:1153537
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    References listed on IDEAS

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    1. Anastasiya SHEVTSOVA & Ivan NOVIKOV & Alexey BOROVSKOY, 2015. "Research of influence of time of reaction of the driver on the calculation of the capacity of the highway," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 10(3), pages 53-59, September.
    2. Xiaoyuan Wang & Shijie Liu & Huili Shi & Hui Xiang & Yang Zhang & Guowen He & Hanqing Wang, 2022. "Impact of Penetrations of Connected and Automated Vehicles on Lane Utilization Ratio," Sustainability, MDPI, vol. 14(1), pages 1-17, January.
    3. Bansal, Prateek & Kockelman, Kara M., 2017. "Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 49-63.
    4. Yunze Wang & Ranran Xu & Ke Zhang, 2022. "A Car-Following Model for Mixed Traffic Flows in Intelligent Connected Vehicle Environment Considering Driver Response Characteristics," Sustainability, MDPI, vol. 14(17), pages 1-17, September.
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