This study introduces a trajectory planning framework for autonomous vehicles utilizing the Frenet coordinate, highlighting on maneuverability and safety in urban environments. The framework incorporates an improved A * algorithm for velocity curve planning and a lateral trajectory sampling method. An interactive risk perception model abstracts the vehicle's trajectory into adjustable frames and dynamically defines the risk area to facilitate real-time collision avoidance. This method allows for adaptive trajectory planning by incorporating a predictive interaction model that anticipates the movements of other traffic participants. Simulation results demonstrate the effectiveness of the framework in real-time scenario simulations, highlighting its potential to improve the safety and efficiency of autonomous vehicles navigation in urban settings.


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    Titel :

    Trajectory Planning for Autonomous Vehicles Based on Interactive Risk Perception and Prediction


    Beteiligte:
    Chen, Bowen (Autor:in) / Chen, Zheng (Autor:in) / Zheng, Jia (Autor:in) / Jiang, Zhangnan (Autor:in)


    Erscheinungsdatum :

    25.10.2024


    Format / Umfang :

    4768444 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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