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.
Trajectory Planning for Autonomous Vehicles Based on Interactive Risk Perception and Prediction
25.10.2024
4768444 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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