In order to solve the problem of weak ability of intelligent vehicles to handle dynamic complex scenes and poor real-time performance on structured roads, a hierarchical spatio-temporal coupled trajectory planning method is designed based on the reachable set method to complete the vehicle’s dynamic uncertainty scenarios trajectory planning. Firstly, based on the status information of the vehicle and surrounding obstacles, the location distribution probability of obstacles in the future is predicted, and the reachable area at each time is calculated based on the reachable set method, and the optimal driving corridor and an initial trajectory are obtained. Secondly, the quadratic programming method is used to optimize the initial trajectory within the optimal driving corridor, and a smooth trajectory is obtained, and the trajectory is tracked. Finally, a simulation platform is built using PreScan, CarSim and Matlab software, simulation analysis is conducted under dynamic and complex traffic scenarios, and obstacle avoidance testing is conducted on the real vehicle platform. The results show that the designed planning method can effectively handle dynamic uncertain scenarios, plan efficient traffic trajectories while ensuring safety, and can also take into account prediction accuracy and real-time performance.
ZHOU Honglong, PEI Xiaofei, LIU Yiping, ZHAO Kefan.
Study on Spatio-temporal Coupled Hierarchical Trajectory Planning of Autonomous Vehicles for Dynamic Uncertain Scenarios[J]. Journal of Mechanical Engineering, 2024, 60(10): 222-234 https://doi.org/10.3901/JME.2024.10.222
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