This article focuses on signalless intersections as the target scenario, categorizes conflict scenarios during cooperative straight-ahead driving of queues, and proposes an overall framework for inter-queue cooperative straight-ahead driving, leveraging the features of intelligent connected vehicle systems. Based on the varying conflict positions between the decision vehicles in the cooperative straight-ahead queue and the queue in the opposite direction, the intersection traffic scenarios are divided into four types and classified into two categories: with conflict and without conflict. To facilitate cooperative driving of the queues in these four scenarios, an overall framework is proposed, supported by a communication decision layer and a control layer. In the communication decision layer for cooperative straight-ahead driving of queues, four communication topologies for information flow are designed, and conflict resolution strategies are formulated as the switching modes for inter-queue cooperative straight-ahead driving at intersections. In each mode, the decision vehicle utilizes an objective optimization function to plan the optimal control inputs for the vehicles, adjusting the speed and spacing of vehicles in each queue, thereby enabling the two queues to safely pass through the intersection conflict zone in a staggered manner. In the cooperative control layer, a hierarchical control approach is adopted, with separate designs for upper and lower layer controllers. This study offers a theoretical foundation and technical support for intelligent connected vehicles to achieve efficient and safe cooperative straight-ahead driving at signalless intersections, significantly advancing the development and application of intelligent connected vehicle technology.


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    Title :

    Research on collaborative direct control strategy for intelligent connected vehicle queue


    Contributors:
    Hu, Liang (editor) / Liu, Chunhui (author) / Qiao, Huaying (author)

    Conference:

    International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2024) ; 2024 ; Shenyang, China


    Published in:

    Proc. SPIE ; 13555 ; 135551E


    Publication date :

    2025-04-18





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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