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Fundamental diagram of mixed traffic flow of CAVs with different connectivity and automation levels

Author

Listed:
  • Jiang, Yangsheng
  • Chen, Hongyu
  • Cong, Hongwei
  • Wu, Yunxia
  • Yao, Zhihong

Abstract

This paper proposes the fundamental diagram model for a mixed traffic flow environment that considers different car-following modes under various levels of automation and connectivity. First, the SAE classification of vehicle automation levels, from L0 to L5, has been further divided into connectivity and automation levels. Second, the car-following modes that affect car-following characteristics are analyzed in mixed traffic flow with different levels of connectivity and automation. Different car-following models are used to describe the car-following characteristics of different types of modes. Third, the fundamental diagram model of mixed traffic flow is further derived based on the different levels of automation and connectivity. Finally, a numerical experiment is designed to evaluate the impact of different penetration rates (PRs) of the car-following modes on the traffic capacity of the mixed traffic flow. The results show that (1) with a higher PR of the automation level of the vehicle, the greater the traffic capacity. At the same time, as the automation levels increase, the change in the penetration rate of high automation levels has a more and more significant impact on traffic capacity. (2) Traffic capacity increases with increased PR of higher automation levels, representing an increase of approximately 11.1 % (3) Compared with connectivity, the PR of automation levels significantly impacts traffic capacity, which is approximately 52.6 %.

Suggested Citation

  • Jiang, Yangsheng & Chen, Hongyu & Cong, Hongwei & Wu, Yunxia & Yao, Zhihong, 2024. "Fundamental diagram of mixed traffic flow of CAVs with different connectivity and automation levels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 646(C).
    • Handle: RePEc:eee:phsmap:v:646:y:2024:i:c:s0378437124004138
    DOI: 10.1016/j.physa.2024.129904
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