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Traffic dynamics around freeway merging area with mixed conventional vehicles and connected and autonomous vehicles

Author

Listed:
  • Dewen Kong

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, P. R. China)

  • Lishan Sun

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, P. R. China)

  • Yingda Chen

    (Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, P. R. China)

Abstract

The mixed traffic of conventional vehicles (CVs) and connected and autonomous vehicles (CAVs) will dominate a long period in the popularization of CAVs and its dynamics are still not clear, especially in some complicated traffic scenarios. In this paper, an improved cellular automaton model was applied to investigate the CVs–CAVs mixed traffic dynamics around freeway merging area. The lane-changing rules were improved to consider the difference between CAVs and CVs and also the variation of drivers’ aggressive driving during the merging process. The simulation has been conducted with different traffic demands and percentages of CAVs while the phase diagram, spatial-temporal diagram, characteristics of traffic volume, velocity profiles, stability and traffic conflict around the merging area were obtained. The results show that CAVs contribute to improving the traffic operation of freeway merging area in most conditions. However, more CAVs in the merging area without proper management will have a negative impact on traffic if the traffic demand for the main road is great. For example, the stability can decrease and particularly, the on-ramp traffic will be completely blocked when the percentage of CAVs is one. The findings can provide a basis for further research on the CVs–CAVs mixed traffic.

Suggested Citation

  • Dewen Kong & Lishan Sun & Yingda Chen, 2022. "Traffic dynamics around freeway merging area with mixed conventional vehicles and connected and autonomous vehicles," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 33(10), pages 1-22, October.
    • Handle: RePEc:wsi:ijmpcx:v:33:y:2022:i:10:n:s0129183122501285
    DOI: 10.1142/S0129183122501285
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    Cited by:

    1. Chen, Yingda & Li, Keping & Zhang, Lun & Chen, Yili & Xiao, Xue, 2024. "Modeling and analysis of mixed traffic flow capacity and stability considering human-driven vehicle drivers' trust attitude towards intelligent connected vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).

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