无人驾驶车辆路径规划算法综述  

Review of path planning algorithm for unmanned vehicles

作　　者：李永丹 马天力[1] 陈超波[1] 韦宏利[1] 杨琼楠 Li Yongdan;Ma Tianli;Chen Chaobo;Wei Hongli;Yang Qiongnan(School of Electronic Information Engineering, Xi'an Technological University, Xi'an 710021,China)

机构地区：[1]西安工业大学电子信息工程学院

出　　处：《国外电子测量技术》2019年第6期72-79,共8页Foreign Electronic Measurement Technology

摘　　要：路径规划作为无人驾驶领域重点研究问题之一,近年来越来越受到人们的关注。在深入研究路径规划的基础上,对现有路径规划算法进行了分析。首先介绍了传统算法、智能优化算法、基于强化学习的算法和混合算法4类路径规划算法;然后,分别从算法的实时性、鲁棒性及时间复杂度三方面比较分析了各算法的性能;最后,对无人驾驶车辆路径规划算法的未来发展趋势进行了展望。In the filed of auto no mous driving, path planning is one of the research focuses and it has received more and more attention in recent years.This paper reviews the existing path planningalgorithms based on in-depth study on the path planning. First, the paper introduceingfour kinds of path planning algorithms the Traditional algorithm, intelligent optimization algorithm, the algorithm based on reinforcement learning and hybrid algorithm. Then, analyzing the performance of each algorithm from the real-time, robustness and time complexity of the algorithm.Finally. we have a discussion and provide insights for future.

关 键 词：无人驾驶车辆 路径规划算法 A*算法 RRT算法 触须算法 强化学习 

分 类 号：TP2[自动化与计算机技术—检测技术与自动化装置]