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Managing merging from a dedicated CAV lane into a conventional lane considering the stochasticity of connected human-driven vehicles

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  • Wu, Guohong
  • Wu, Jiaming
  • Zheng, Shiteng
  • Jiang, Rui

Abstract

Connected and automated vehicle (CAV) provides a new promising solution for transportation system. Despite the promising future of CAV, fully deployment of CAV on current road systems is still challenging and the coexistence of CAV and human-driven vehicle (HDV) is inevitable. Furthermore, most studies for trajectory planning under mixed traffic ignore the stochasticity of human-driven vehicle (HDV), which is unrealistic and causes infeasible planned trajectory. In this study, we investigate merging control from a dedicated CAV lane into a conventional lane. The stochastic mixed traffic cooperative merging problem is formulated as a mixed integer quadratic constraint programming, which optimizes vehicle longitudinal trajectories and lane-changing maneuvers in a centralized way. Rolling horizon framework coupled with car-following and lane-changing execution algorithms is used to address the stochasticity of connected human-driven vehicle (CHV). Simulation results validate our proposed control strategy outperforms the rule-based control strategy from the perspective of traffic efficiency, lane-changing efficiency, fuel economy and driving comfort. The robustness of rolling horizon framework and sensitivity analysis are also conducted. Finally, the vehicle trajectory comparison intuitively shows the difference between 2 control strategies.

Suggested Citation

  • Wu, Guohong & Wu, Jiaming & Zheng, Shiteng & Jiang, Rui, 2024. "Managing merging from a dedicated CAV lane into a conventional lane considering the stochasticity of connected human-driven vehicles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 652(C).
    • Handle: RePEc:eee:phsmap:v:652:y:2024:i:c:s0378437124005533
    DOI: 10.1016/j.physa.2024.130044
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    References listed on IDEAS

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