This paper proposes a two-stage multi-lane unsignalized intersection cooperative control strategy based on mixed platoons (MICS-PF) in the mixed traffic environment of connected automated vehicles (CAVs) and connected human-driven vehicles (CHVs). In the first stage, we propose a 0–1 integer programming model based on vehicles’ intersection movements and potential car-following costs to organize vehicles into mixed platoons led by CAVs. Meanwhile, we design a rule-based algorithm to coordinate the relative distribution of platoons. Then, the lane-changing and car-following models are integrated to ensure that the platoons organization plan can be completed in the limited functional zone. In the second stage, we design an improved minimum covering clique algorithm to generate a conflict-free passing order of platoons by considering the platoon-level conflict relation and the potential yield delay. The proposed strategy couples the process of organizing vehicles into mixed platoons to pass through the intersection. The optimal platoon organization enables CHVs to receive accurate guidance when entering the intersection and avoids the disorderly lane change at the upstream road sections. The mixed platoon control also allows vehicles to avoid stop-and-go, improve the capacity of approach roads, and prevent the intersection capacity from being restricted by the inefficient traffic at the approach road. The conflict-free coordination method of mixed platoons optimizes the throughput of intersections and broadens the usage conditions of unsignalized intersections. A series of simulation experiments verify the effectiveness of the strategy, and the applicable boundary conditions are obtained.


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    Title :

    Multi-Lane Unsignalized Intersection Cooperation Strategy Considering Platoons Formation in a Mixed Connected Automated Vehicles and Connected Human-Driven Vehicles Environment


    Contributors:
    Wu, Ruiyi (author) / Jia, Hongfei (author) / Huang, Qiuyang (author) / Tian, Jingjing (author) / Gao, Heyao (author) / Wang, Guanfeng (author)


    Publication date :

    2024-02-01


    Size :

    3097802 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English