Path Planning Algorithms for Smart Parking: Review and Prospects

IF 2.6 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Zhonghai Han, Haotian Sun, Junfu Huang, Jiejie Xu, Yu Tang, Xintian Liu
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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.
智能停车的路径规划算法:回顾与展望
路径规划算法是智能停车过程中的重要组成部分。目前,为智能停车设计的路径规划算法有很多。设计合理的路径规划算法对智能停车的效率有着重要影响。首先,本文全面介绍了四种路径规划算法的原理和步骤:Dijkstra算法(包括其优化导数)、A*算法(包括其优化导数)、RRT(快速探索随机树)算法(包括其优化导数)和BFS(广度优先搜索)算法。其次,利用 Dijkstra 算法、A* 算法、BFS 算法和动态加权 A* 算法来规划智能停车过程所需的路径。在分析过程中发现,Dijkstra 算法在智能停车的路径规划中存在规划路径迂回、耗时过长等缺点。虽然基于 Dijkstra 算法的传统 A* 算法大大缩短了规划时间,但路径规划效果仍不理想。在四种算法中,BFS(广度优先搜索)算法的规划时间最短,但其规划的路径不稳定,不是最优路径。动态加权 A* 算法能取得较好的路径规划效果,而且通过调整权重值,该算法具有很好的适应性。本综述为进一步研究智能停车过程中的路径规划算法提供了参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
World Electric Vehicle Journal
World Electric Vehicle Journal Engineering-Automotive Engineering
CiteScore
4.50
自引率
8.70%
发文量
196
审稿时长
8 weeks
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