算法的无人车路径规划  

Autonomous Vehicle Dynamic Path Planning Based on Improved A*and DWA Algorithms

作　　者：许柳柳 杨爱喜 臧豫徽 XU Liuliu;YANG Aixi;ZANG Yuhui(School of Mechanical and Automotive Engineering,Anhui Polytechnic University,Wuhu 241000,China;Zhejiang Asia Pacific Intelligent Network Automobile Innovation Center Co.,Ltd.,Hangzhou 311203,China;Polytechnic Institute of Zhejiang University,Hangzhou 310015,China)

机构地区：[1]安徽工程大学机械与汽车工程学院,安徽芜湖241000 [2]浙江亚太智能网联汽车创新中心有限公司,浙江杭州311203 [3]浙江大学工程师学院,浙江杭州310015

出　　处：《安徽工程大学学报》2025年第1期1-7,30,共8页Journal of Anhui Polytechnic University

基　　金：浙江省科技计划项目(2022C04023)。

摘　　要：针对A*算法搜索效率低和无法随机躲避障碍物的路径规划问题,提出了融合改进A*算法与DWA算法。首先对于A*算法搜索效率低的问题,通过改进算法启发函数,引入安全距离参数,在寻路过程中去除多余节点,转折点也随之减少,搜索效率提高的同时更有利于无人车平稳行驶。对于A*算法无法随机躲避动态障碍物的问题,通过将改进后的A*算法与DWA算法融合,结合两种算法的优点,使规划的路径不仅可以随机躲避动态障碍物,并且可以沿着规划好的全局路径行驶,从而避免出现陷入局部最优的情况。由仿真结果可知,改进后的A*算法的搜索效率随着地图大小和环境复杂程度的增加而不断提高,搜索效率最高为80.73%。最后对比三种不同算法的仿真结果,融合算法规划的路径更短,搜索效率更高,搜索效率与传统DWA算法和蚁群算法相比分别提升了40.68%和32.28%。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 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]