A Topological Map-based Path Coordination Strategy for Autonomous Parking 2019-01-0691
This paper proposed a path coordination strategy for autonomous parking based on independently designed parking lot topological map. The strategy merges two types of paths at the three stages of path planning, to determinate vehicle pose, position and mode switching timing between low-speed automated driving and automated parking. Firstly, based on the prerequisite that parking spaces should be parallel or vertical to a corresponding path, a topological parking lot map is designed by using the point cloud data collected by LiDAR sensor. This map is consist of road node coordinates, adjacent matrix and parking space information. Secondly, the direction and lateral distance of the parking space to the last node of global path are used to decide parking type and direction at parking planning stage. Finally, the parking space node is used to connect global path and parking path at path coordination stage. After optimizing nodes and smoothing path, those two types of paths can be merged without deviation. The experiments show that the proposed topological map-based path planning method can effectively generate a feasible path to guide vehicle from the drop off zone to the desired parking space. At the same time, continuous curvature variation of path and steady speed can improve accuracy of path tracking.