This paper addresses the challenge of trajectory planning from the parking lot’s entry to the assigned parking spot in the narrow parking environment.The trajectory planning methods for narrow scenarios encounter sub...This paper addresses the challenge of trajectory planning from the parking lot’s entry to the assigned parking spot in the narrow parking environment.The trajectory planning methods for narrow scenarios encounter substantial challenges related to searching time,the establishment of obstacle-avoidance constraint and path smoothness.An improved hybrid A^(*)(IHA)algorithm based on creative selection of intermediate points is proposed to address those issues and enhance the overall trajectory planning performance.The traditional A^(*)search is firstly established to quickly generate a global,coarse path and recognize the sequential waypoints with the same heading angles.The last waypoint in each such sequence is then creatively selected as the intermediate point.Throughout the global coarse path,all the intermediate points are connected with the start and end points using hybrid A^(*)to obtain the feasible trajectory for the narrow environment.Checking the searching time required between all the two sequential intermediate points throughout the trajectory,the last point of such sequence can be reasonably deleted for further improvement of planning efficiency.Moreover,tackling the problem of small drivable area of vehicle in the narrow scenarios,a new adaptive collision-avoidance constraint is designed to facilitate the optimization process.Based on this,an optimal control problem is finally formulated to generate the optimal trajectory ensuring smoothness and parking efficiency for the autonomous vehicles.Both the simulation and experimental results have demonstrated the efficiency and reliability of the proposed trajectory planning method.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 62388101,Grant 62303011 and Grant 62303010in part by the Anhui Provincial Key Research Program of Universities under Grant 2022AH050087in part by University Synergy Innovation Program of Anhui Province under Grant GXXT-2023-039.
文摘This paper addresses the challenge of trajectory planning from the parking lot’s entry to the assigned parking spot in the narrow parking environment.The trajectory planning methods for narrow scenarios encounter substantial challenges related to searching time,the establishment of obstacle-avoidance constraint and path smoothness.An improved hybrid A^(*)(IHA)algorithm based on creative selection of intermediate points is proposed to address those issues and enhance the overall trajectory planning performance.The traditional A^(*)search is firstly established to quickly generate a global,coarse path and recognize the sequential waypoints with the same heading angles.The last waypoint in each such sequence is then creatively selected as the intermediate point.Throughout the global coarse path,all the intermediate points are connected with the start and end points using hybrid A^(*)to obtain the feasible trajectory for the narrow environment.Checking the searching time required between all the two sequential intermediate points throughout the trajectory,the last point of such sequence can be reasonably deleted for further improvement of planning efficiency.Moreover,tackling the problem of small drivable area of vehicle in the narrow scenarios,a new adaptive collision-avoidance constraint is designed to facilitate the optimization process.Based on this,an optimal control problem is finally formulated to generate the optimal trajectory ensuring smoothness and parking efficiency for the autonomous vehicles.Both the simulation and experimental results have demonstrated the efficiency and reliability of the proposed trajectory planning method.
