A Method for Autonomous Driving Trajectory Planning in Parking Environments - LIN Chun, HE Yuesheng, FANG Xingqi, WANG Chunxiang (Shanghai Jiaotong Daxue xuebao, 2023)
Local trajectory planning is one of the key technologies of the autonomous valet parking system. In this scenario, there exist problems such as long planning time, discontinuous curvature, and insufficient safety in local trajectory planning methods for intelligent vehicles. Aimed at these problems, this paper proposes a trajectory planning method for intelligent vehicles in parking scenarios. This method improves the real-time performance and security of the initial path search by improving the analytic expansions of the hybrid A* algorithm and introducing the risk function. Further, according to the initial path, the quadratic programming method is used to realize path smoothing and speed planning. Finally, the trajectory generation is completed. Simulation experiments show that the method can improve the real-time, smoothness, and safety of intelligent vehicle trajectory planning. In addition, in actual parking environment, the feasibility of the method is verified in real-world vehicle experiments.