Path Planning Algorithms for Smart Parking: Review and Prospects

Author:

Han Zhonghai1,Sun Haotian2,Huang Junfu1,Xu Jiejie3,Tang Yu1,Liu Xintian2ORCID

Affiliation:

1. China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China

2. School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China

3. Shanghai Smart Vehicle Cooperation Innovation Center, Shanghai 201805, China

Abstract

Path planning algorithms are crucial components in the process of smart parking. At present, there are many path planning algorithms designed for smart parking. A well-designed path planning algorithm has a significant impact on the efficiency of smart parking. Firstly, this paper comprehensively describes the principles and steps of four types of path planning algorithms: the Dijkstra algorithm (including its optimized derivatives), the A* algorithm (including its optimized derivatives), the RRT (Rapidly exploring Random Trees) algorithm (including its optimized derivatives), and the BFS (Breadth First Search) algorithm. Secondly, the Dijkstra algorithm, the A* algorithm, the BFS algorithm, and the Dynamic Weighted A* algorithm were utilized to plan the paths required for the process of smart parking. During the analysis, it was found that the Dijkstra algorithm had the drawbacks of planning circuitous paths and taking too much time in the path planning for smart parking. Although the traditional A* algorithm based on the Dijkstra algorithm had greatly reduced the planning time, the effect of path planning was still unsatisfactory. The BFS (Breadth First Search) algorithm had the shortest planning time among the four algorithms, but the paths it plans were unstable and not optimal. The Dynamic Weighted A* algorithm could achieve better path planning results, and with adjustments to the weight values, this algorithm had excellent adaptability. This review provides a reference for further research on path planning algorithms in the process of smart parking.

Publisher

MDPI AG

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