计算机科学 ›› 2024, Vol. 51 ›› Issue (4): 334-343.doi: 10.11896/jsjkx.221200079
朱威, 杨世博, 滕帆, 何德峰
ZHU Wei, YANG Shibo, TENG Fan, HE Defeng
摘要: 针对传统无人车轨迹规划算法在非结构化场景下存在实时性较低和轨迹平滑性较差等问题,提出了一种前后端分离的轨迹规划算法。该算法的前端路径搜索部分对Hybrid A*算法在控制空间进行搜索范围的剪枝且保留了车辆的运动学约束,并通过优化启发函数的计算方式,提高了图搜索的实时性。该算法的后端轨迹优化部分分为两个阶段:第一阶段设计了一个软约束非线性多目标优化器对路径进行局部优化,生成离散的轨迹位姿点和时间分配值;第二阶段基于五次样条曲线利用最小化Jerk的思想对离散位姿点进行平滑连接,提高了轨迹的平滑性。最后在室外停车场环境下对所提算法进行了实车测试,前端路径搜索和后端轨迹优化的实验结果表明该算法具有较高的实时性和轨迹平滑性。
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[1]KIM D,KIM H,HUH K.Local trajectory planning and control for autonomous vehicles using the adaptive potential field[C]//IEEE Conference on Control Technology and Applications(CCTA).IEEE,2017:987-993. [2]WEI J.Autonomous vehicle social behavior for highway driving[D].Pittsburgh:Carnegie Mellon University,2017. [3]SUN Q,WANG C,FU R,et al.Lane change strategy analysis and recognition for intelligent driving systems based on random forest[J].Expert Systems with Applications,2021,186:115781. [4]WANG Z Q,HU X G,LI X,DU Z Q.Overview of Global Path Planning Algorithms for Mobile Robots[J].Computer Science,2021,48(10):19-29. [5]JIN X,YAN Z,YANG H,et al.A Practical Sampling-based Motion Planning Method for Autonomous Driving in Unstructured Environments[J].IFAC-Papers OnLine,2021,54(10):449-453. [6]JIA C X,LUO Q,GONG Y Y.Obstacle Avoidance Path Planning for Irregular Obstacles[J].Computer Science,2017,44(9):290-295. [7]LIU D,NIE Z G,ZHOU Y.Research on the local trajectory planning method for intelligent vehicles in a complex traffic environment[J].Journal of Chongqing University of Technology(Natural Science),2023,37(4):39-49. [8]ZHANG W,ZHANG S P,LUO C E,et al.Collision avoidance trajectory planning for intelligent vehicles in emergency conditions[J].Journal of Jilin University(Engineering and Technology Edition),2022,52(07):1515-1523. [9]FAN H,ZHU F,LIU C,et al.Baidu apollo em motion planner[J].arXiv:1807.08048,2018. [10]ZHANG Y,SUN H,ZHOU J,et al.Optimal trajectory generation for autonomous vehicles under centripetal acceleration constraints for in-lane driving scenarios[C]//IEEE Intelligent Transportation Systems Conference(ITSC).IEEE,2019:3619-3626. [11]HAN Y Q,ZHANG K,BIN Y,et al.Convex approximationbased avoidance theory and path planning mpc for driverless vehicles[J].Acta Automatic Sinica,2020,46(1):153-167. [12]DING W,ZHANG L,CHEN J,et al.Safe Trajectory Generation for Complex Urban Environments Using Spatio-temporal Semantic Corridor[J].IEEE Robotics and Automation Letters,2019,4(3):2997-3004. [13]WOLF P,KURZER K,WINGERT T,et al.Adaptive behavior generation for autonomous driving using deep reinforcement learning with compact semantic states[C]//IEEE Intelligent Vehicles Symposium(IV).IEEE,2018:993-1000. [14]XU Z,TANG C,TOMIZUKA M.Zero-shot deep reinforcement learning driving policy transfer for autonomous vehicles based on robust control[C]//International Conference on Intelligent Transportation Systems(ITSC).IEEE,2018:2865-2871. [15]ROSBACH S,JAMES V,GROBJOHANN S,et al.Driving with style:Inverse reinforcement learning in general-purpose planning for automated driving[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS).IEEE,2019:2658-2665. [16]RODRIGUEZ S,TANG X,LIEN J M,et al.An obstacle-based rapidly-exploring random tree[C]//Proceedings 2006 IEEE International Conference on Robotics and Automation.IEEE,2006:895-900. [17]LEE J W,KNOW O,ZHANG L J,et al.A Selective Retraction-Based RRT Planner for Various Environments[J].IEEE Transa-ctions on Robotics:A publication of the IEEE Robotics and Automation Society,2014,30(4):1002-1011. [18]WOIF M T,BUEDICK J W.Artificial potential functions forhighway driving with collision avoidance[C]//IEEE International Conference on Robotics and Automation(ICRA).IEEE,2008:3731-3736. [19]MCFETRIDGE L,IBRAHIM M Y.A new methodology of mobile robot navigation:The agoraphilic algorithm[J].Robotics and Computer-Integrated Manufacturing,2009,25(3):545-551. [20]MONTIEL O,OROZCO-ROSAS U,SEPULVEDA R.Pathplanning for mobile robots using Bacterial Potential Field for avoiding static and dynamic obstacles[J].Expert Systems with Applications,2015,42(12):5177-5191. [21]ZHANG Q,CHEN D,CHEN T.An obstacle avoidance method of soccer robot based on evolutionary artificial potential field[J].Energy Procedia,2012,16:1792-1798. [22]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. [23]LIU Z L,LI Y S,ZHENG L.Local Path Planning for Autonomous Vehicles Based on Sparse Representation of Point Cloud in Unstructured Environments[J].Journal of Mechanical Engineering,2020,56(2):163-173. [24]HART P E,NILSSON N J,RAPHAEL B.A formal basis forthe heuristic determination of minimum cost paths in graphs[J].IEEE Transactions on Systems Science and Cybernetics,1968,4(2):100-107. |
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