As a critical driving scenario, emergency collision avoidance (CA) is challenging and necessary for both human drivers and automated vehicles. Compared to passenger cars, the complexity of tractor-trailer vehicle dynamics makes it more difficult to implement CA features, especially when designing the motion planning module. Using traditional planning methods, it is difficult to balance optimality, safety and real-time performances. To address these needs, this study proposes an optimal-control-problem (OCP) based framework of motion planning for tractor-trailer vehicles, with specific focuses on the fast solution of OCP that considers nonlinear vehicle model, state constraints and roll-over stability limits. Inspired by expert drivers’ experience in planning within a previewed distance and then keeping updating, the original time-domain OCP with free terminal time is transformed into a space-domain OCP with fixed length, which can achieve fast, robust and forward-looking motion planning. Simulations and scaled vehicle experiments show that the planning algorithm performs safely and efficiently under different speed and road adhesion conditions.


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    Title :

    Optimal and Real-Time Planning for Emergency Collision Avoidance of Tractor-Trailer Vehicles


    Additional title:

    Lect.Notes Mechanical Engineering


    Contributors:
    Huang, Wei (editor) / Ahmadian, Mehdi (editor) / Li, Daofei (author) / Jiang, Xin (author) / Pan, Hao (author) / Zhang, Jiajie (author)

    Conference:

    The IAVSD International Symposium on Dynamics of Vehicles on Roads and Tracks ; 2023 ; Ottawa, ON, Canada August 21, 2023 - August 25, 2023



    Publication date :

    2024-10-13


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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