Review on Local Path Planning Algorithm for Intelligent Vehicle

doi:10.16638/j.cnki.1671-7988.2022.023.043

Abstract

Abstract: In order to improve the driving stability and rationality of intelligent vehicles, this paper classifies and summarizes the local path planning algorithms commonly used by intelligent vehicles in recent years. Firstly, this paper expounds the principles of various traditional algorithms, analyzes their advantages and disadvantages, and points out the shortcomings of traditional algorithms in the application of intelligent vehicles. Secondly, this paper sorts out and analyzes the improved algorithms proposed by scholars when various traditional algorithms are applied to intelligent vehicles. Finally, it is proposed that the algorithm based on discrete optimization is the application trend of intelligent vehicle local path planning in the future, and the fusion of multiple algorithms is the research direction of intelligent vehicle local path planning in complex scenarios. The research results of this paper can provide reference for researchers in the field of intelligent vehicles when choosing local path planning algorithms.

Key words: Intelligent vehicle; Path planning algorithm; Local path planning; Discrete optimization; Fusion of multiple algorithms

摘要： 为提高智能车辆行驶的平稳性和合理性，文章对近年来智能车辆常用的局部路径规划算法进行了分类和总结。首先对各类传统算法的原理进行了阐述，分析其优缺点，并指出传统算法在智能车辆上应用时的不足；其次整理分析了各类传统算法应用至智能车辆上时各学者所提出的改进算法；最后提出基于离散优化的算法是未来智能车辆局部路径规划的应用趋势，多算法融合是复杂场景下智能车辆局部路径规划的研究方向。文章的研究结果为智能车领域的研究人员在选择局部路径规划算法时提供参考。

关键词: 智能车辆；路径规划算法；局部路径规划；离散优化；多算法融合

MA Xiaolu. Review on Local Path Planning Algorithm for Intelligent Vehicle[J]. Automobile Applied Technology, 2022, 47(23): 232-237.

马晓录. 智能车辆局部路径规划算法研究综述[J]. 汽车实用技术, 2022, 47(23): 232-237.

References

[ 1 ] 郑凯林,韩宝玲,王新达.基于改进 TEB算法的阿克曼机器人运动规划系统[J].科学技术与工程,2020,20 (10):3997-4003. [ 2 ] 彭晓燕,谢浩,黄晶.无人驾驶汽车局部路径规划算法研究[J].汽车工程,2020,42(1):1-10. [ 3 ] KHATIB O.Real-time Obstacle Avoidance System for Manipulators and Mobile Robots[J].The International Journal of Robotics Research,1986,5(1):90-98. [ 4 ] 余政.基于改进人工势场法的智能汽车超车轨迹规划策略[J].农业装备与车辆工程,2021,59(9):64-68. [ 5 ] 朱毅,张涛,宋靖雁.未知环境下势场法路径规划的局部极小问题研究[J].自动化学报,2010,36(8):1122-1130. [ 6 ] 陈宇珂,林棻,王少博.基于障碍物势场和模型预测的车辆避障路径规划[J].重庆理工大学学报(自然科学),2020,34(10):34-41. [ 7 ] 修彩靖,陈慧.基于改进人工势场法的无人驾驶车辆局部路径规划的研究[J].汽车工程,2013,35(9):808- 811. [ 8 ] 安林芳,陈涛,成艾国,等.基于人工势场算法的智能车辆路径规划仿真[J].汽车工程,2017,39(12):1451-1456. [ 9 ] 吴乙万,黄智.基于动态虚拟障碍物的智能车辆局部路径规划方法[J].湖南大学学报(自然科学版),2013, 40(1):33-37. [10] GU X, HAN M, ZHANG W, et al.Intelligent Vehicle Path Planning Based on Improved Artificial Potential Field Algorithm[C]//2019 International Conference on High Performance Big Data and Intelligent Systems. New York:IEEE,2019:104-109. [11] RASEKHIPOUR Y,KHAJEPOUR A,CHEN S K,et al. A Potential Field-based Model Predictive Path-planning Controller for Autonomous Road Vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2017,18(5): 1255-1267. [12] GUO Q,ZHENG Z,YUE X.Path-planning of Automated Guided Vehicle Based on Improved Dijkstra Algorithm[C]//2017 29h Chinese Control & Decision Conference.New York:IEEE,2017:7138-7143. [13] 徐瑞,李军.无人驾驶汽车局部路径规划研究综述[J]. 汽车科技,2020(5): 84-89. [14] 马飞,杨皞屾,顾青,等.基于改进 A*算法的地下无人铲运机导航路径规划[J].农业机械学报,2015,46(7): 303-309. [15] 李琼琼,施杨洋,布升强,等.基于改进 A*算法的无人车路径规划研究[J].林业机械与木工设备,2020,48 (6):45-49. [16] 张毅,施明瑞.基于单元分解的改进 D* lite 路径规划算法[J].重庆邮电大学学报(自然科学版),2021,33(6): 1007-1013.[17] DOLGOV D, THRUN S, MONTEMERLO M, et al. Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments[J].The International Journal of Robotics Research,2010,29(5):485-501. [18] 齐尧,徐友春,李华,等.一种基于改进混合 A*的智能车路径规划算法[J].军事交通学院学报,2018,20(8): 85-90. [19] 杨瑶,付克昌,蒋涛,等.一种改进 A*算法在智能车中的应用研究[J].重庆理工大学学报(自然科学),2021, 35(3):71-79. [20] 田海波,李陆军,畅科剑,等.用于无人车路径规划的改进 A*算法[J].现代制造工程,2021(11):63-68,92. [21] 辛煜,梁华为,杜明博,等.一种可搜索无限个邻域的改进 A*算法[J].机器人,2014,36(5):627-633. [22] 刘晓涛,蔡云飞,王田橙.基于 SVM 的受约束 D*算法在无人车寻路中的应用[J].计算机与数字工程,2017, 45(9): 1748-1754. [23] DAKULOVI? M, PETROVI? I.Two-way D*Algorithm for Path Planning and Replanning[J].Robotics and Autonomous Systems,2011,59(5):329-342. [24] FERGUSON D,STENTZ A.Field D*:An InterpolationBased Path Planner and Replanner[M].Berlin Springer, 2007. [25] KAVRAKI L E,SVESTKA P, LATOMBE J C, et al. Probabilistic Roadmaps for Path Planning in Highdimensional Configuration Spaces[J].IEEE Transactions on Robotics and Automation,1996,12(4):566-580. [26] 邹善席,王品,韩旭.基于 PRM 改进的路径规划算法 [J].组合机床与自动化加工技术,2019(1):1-3. [27] LAVALLE S M. Rapidly-exploring Random Trees:A New Tool for Path Planning[J].Research Report,1999. [28] 宋晓琳,周南,黄正瑜,等.改进 RRT 在汽车避障局部路径规划中的应用[J].湖南大学学报(自然科学版), 2017,44(4):30-37. [29] KARAMAN S,FRAZZOLI E.Sampling-based Algorithms for Optimal Motion Planning[J].The International Journal of Robotics Research,2011,30(7):846-894. [30] 赵港.改进 RRT*算法的智能车辆路径规划[J].汽车实用技术,2021,46(22):41-43. [31] KUFFNER J J,LAVALLE S M.RRT-Connect:An Efficient Approach to Single-query Path Planning[C]//Proceedings of the 2000 IEEE International Conference on Robotics and Automation. New York: IEEE,2000: 995-1001. [32] TAHERI E, FERDOWSI M H, DANESH M. Fuzzy Greedy RRT Path Planning Algorithm in a Complex Configuration Space[J].International Journal of Control, Automation and Systems,2018,16(6): 3026-3035. [33] ELBANHAWI M, SIMIC M. Randomised Kinodynamic Motion Planning for an Autonomous Vehicle in Semi-structured Agricultural Areas[J]. Biosystems Engineering,2014,126:30-44. [34] ZUO L,GUO Q,XU X, et al. A Hierarchical Path Planning Approach Based on A and Least-squares Policy Iteration for Mobile Robots[J].Neurocomputing,2015,170(25): 257-266. [35] 杜明博,梅涛,陈佳佳,等.复杂环境下基于 RRT 的智能车辆运动规划算法[J].机器人,2015,37(4):443-450. [36] 周维,过学迅,裴晓飞,等.基于 RRT 与 MPC 的智能车辆路径规划与跟踪控制研究[J].汽车工程,2020,42 (9):1151-1158. [37] WERLING M,ZIEGLER J,KAMMEL S,et al.Optimal Trajectory Generation for Dynamic Street Scenarios in a Frenet Frame[C]//2010 IEEE International Conference on Robotics and Automation.New York:IEEE, 2010: 987-993. [38] CHU K, LEE M, SUNWOO M. Local Path Planning for Off-road Autonomous Driving with Avoidance of Static Obstacles[J].IEEE Transactions on Intelligent Transportation Systems,2012,13(4):1599-1616. [39] 姜岩,龚建伟,熊光明,等.基于运动微分约束的无人车辆纵横向协同规划算法的研究[J].自动化学报,2013, 39(12):2012-2020. [40] 魏民祥,滕德成,吴树凡.基于 Frenet 坐标系的自动驾驶轨迹规划与优化算法[J].控制决策,2021,36(4): 815-824. [41] 陈成,何玉庆,卜春光,等.基于四阶贝塞尔曲线的无人车可行轨迹规划[J].自动化学报,2015,41(3): 486-496. [42] 张琳,章新杰,郭孔辉,等.未知环境下智能汽车轨迹规划滚动窗口优化[J].吉林大学学报(工学版),2018,48 (3):652-660. [43] ZHANG Y,CHEN H Y,WASLANDER S L,et al.Hybrid Trajectory Planning for Autonomous Driving in Highly Constrained Environments[J].IEEE Access, 2018(6):32800-32819. [44] R?SMANN C,HOFFMANN F,BERTRAM T. Kinodynamic Trajectory Optimization and Control for Car-like Robots[C]//2017 IEEE/RSJ International Conference on Intelligent Robots and Systems.New York:IEEE,2017:5681-5686. [45] 周慧子,胡学敏,陈龙,等.面向自动驾驶的动态路径规划避障算法[J].计算机应用,2017,37(3):883-888.