A path planning and tracking framework based on model predictive control to avoid obstacles is proposed for autonomous vehicles. Firstly, a vehicle in road coordinate system is established to describe the relationship between the vehicle and the reference path. Secondly, to deal with multi obstacles, an efficient search-based method along the reference path is used to build collision-free driving corridors as state constraints. Then, a multi-constrained model predictive controller based on vehicle kinematic and dynamic model is employed to compute the optimal steering angle. Finally, the simulation results show that the proposed path planning and control framework approach are effective for various driving scenarios.


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    Title :

    A Path Planning and Tracking Framework Based on Model Predictive Control for Autonomous Vehicle Obstacle Avoidance


    Additional title:

    Lect.Notes Mechanical Engineering


    Contributors:
    Orlova, Anna (editor) / Cole, David (editor) / Xiong, Lu (author) / Fu, Zhiqiang (author) / Zeng, Dequan (author) / Qian, Zixuan (author) / Leng, Bo (author)

    Conference:

    The IAVSD International Symposium on Dynamics of Vehicles on Roads and Tracks ; 2021 August 17, 2021 - August 19, 2021



    Publication date :

    2022-08-06


    Size :

    7 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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