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On the impacts of dedicated lanes for CAVs in mixed traffic: Evaluation using a modified cell transmission model

Author

Listed:
  • Zhang, Jian
  • Bai, Yan-Zhenni
  • He, Jia
  • Wang, Tao

Abstract

Dedicated lane (DL) for connected and autonomous vehicles (CAVs) is a potential solution to manage mixed traffic flow of CAVs and human-driven vehicles (HVs) in the near future. In this paper, we propose a modified cell transmission model (CTM) to evaluate the performance and efficacy of CAV DLs under different scenarios in mixed traffic environments. We integrate the mixed traffic flow fundamental diagram and logit model to calculate through and lane-change flow. The model specifically considers the capacity drop phenomena and driving rules on DLs. Numerical experiments are conducted on a three-lane circular road to analyze the impacts of number, length, and position of DLs under varying CAV penetration rates and traffic demands on the mixed traffic flow. The experimental results suggest that the greatest benefits are achieved when DLs are implemented under conditions of high traffic demand and low CAV penetration rates. The effectiveness of setting different numbers of DLs varies under different demand levels and penetration rates. In scenarios where lanes have different speed limits, adjusting the horizontal position of the DLs yields more significant effects; setting DLs sequentially from the edge and in adjacent lanes — whether on high-speed or low-speed lanes — is an effective choice. Subsequently, based on the overall utility of the road segment, the conditions for implementing partial DLs are further analyzed. The findings provide insights for maximizing the advantages of CAVs, enhancing the orderliness and stability of mixed traffic flow, and offer a theoretical basis for future CAV DL deployment and traffic management.

Suggested Citation

  • Zhang, Jian & Bai, Yan-Zhenni & He, Jia & Wang, Tao, 2025. "On the impacts of dedicated lanes for CAVs in mixed traffic: Evaluation using a modified cell transmission model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 662(C).
  • Handle: RePEc:eee:phsmap:v:662:y:2025:i:c:s0378437125000706
    DOI: 10.1016/j.physa.2025.130418
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