安徽工程大学学报2025，Vol.40Issue(1)：1-7,30,8.
基于改进A*和DWA算法的无人车路径规划
Autonomous Vehicle Dynamic Path Planning Based on Improved A* and DWA Algorithms
摘要
Abstract
In order to solve the problem that A* algorithm has low searching efficiency and cannot randomly avoid obstacles,A fusion improved A* algorithm and DWA algorithm are proposed.First of all,for the problem of low search efficiency of the A* algorithm,by improving the heuristic function of the algorithm and introducing the safe distance parameter,redundant nodes are removed in the path finding process,and the turning point is also reduced,which is more conducive to the stable running of the unmanned vehicle while the search efficiency is improved.For the problem that A* algorithm cannot randomly avoid dynamic obstacles,by combining the improved A* algorithm with DWA algorithm and combining the advantages of the two algorithms,the planned path can not only randomly avoid dynamic obstacles,but also the vehicle can travel along the planned global path,so as to avoid falling into the local optimal situation.The simulation results show that the search efficiency of the improved A* algorithm increases with the increase of the map size and the complexity of the environment,and the maximum search efficiency is 80.73%.Finally,compared with the simulation results of three different algorithms,the fusion algorithm has shorter path planning and higher search efficiency,and the search efficiency is improved by 40.68%and 32.28%compared with the traditional DWA algorithm and ant colony algorithm,respectively.关键词
路径规划/A*算法/动态窗口法/安全距离参数Key words
path planning/A* algorithm/dynamic window method/safe distance parameter分类
计算机与自动化引用本文复制引用
许柳柳,杨爱喜,臧豫徽..基于改进A*和DWA算法的无人车路径规划[J].安徽工程大学学报,2025,40(1):1-7,30,8.基金项目
浙江省科技计划项目(2022C04023) （2022C04023）
