A novel path planning methodology for automated valet parking based on directional graph search and geometry curve

Abstract

The paper presents a novel path planning methodology based on the directional graph search and the geometry curve for the Automated Valet Parking (AVP) system. The whole path planning methodology is divided into three parts including the global path planning, the path coordination strategy and the parking path planning. Firstly, the global path planning is triggered to find a path from the parking slot entrance to the rough location of the assigned parking spot. A novel directional Hybrid A* algorithm is proposed to generate the global path efficiently without redundant searches, such as the dead end. Afterwards, the path coordination strategy gives a transitional path to connect the end node of the global path to the parking planning start node. The transitional path is composed of geometry curves including arcs and line segments based on the optimal parking start node. Finally, the parking path planning generates a parking path to guide the vehicle from parking start node to the parking space. A modified C-type vertical parking path planning algorithm is utilized to generate the parking path, offering flexibility for choosing the parking start node. Simulation results based on Matlab and PreScan show that it takes less time for the proposed path planning algorithm to generate a feasible path for the AVP system compared with the general planning algorithm. The novel AVP path planning algorithm also has the potential for practical use.