Motion planning for autonomous vehicles not only requires real-time planning of maneuverable trajectories, but also requires it to have good environmental adaptability. This paper takes the intelligent vehicle as the research object, and establishes the kinematics/dynamics model of the vehicle and the kinematics monorail python model. Based on the manipulating automaton generator provided in CommonRoad and the parameters of the vehicle model actually established, a set of motion primitives suitable for general urban roads is generated. Through the improved A* search algorithm, a maneuvering automaton is constructed, and the results show that feasible solutions can be obtained under typical road traffic conditions, and the algorithm is effective and stable.


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    Title :

    Motion Planning of Autonomous Driving Vehicles Based on Search Algorithms and Motion Primitives


    Contributors:
    Jin, Ma (author) / Chen, Xi (author) / Li, Xiaolong (author) / Xia, Kerui (author) / Wu, Zihan (author) / Liu, Yiqun (author) / Zhang, Pinjia (author)

    Conference:

    ECITech 2022 - The 2022 International Conference on Electrical, Control and Information Technology ; 2022 ; Kunming, China


    Published in:

    Publication date :

    2022-01-01


    Size :

    6 pages



    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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