无人驾驶牵引车自主巡航路径规划方法  

Autonomous Cruise Path Planning Method for Autonomous Driverless Vehicles

作　　者：李子奇 吴迪 LI Ziqi;WU Di(Department of Automotive Engineering,Anhui Automobile Vocational and Technical College,Hefei 230601 China;School of Automotive and Transportation Engineering,Hefei University of Technology,Hefei 230000 China)

机构地区：[1]安徽汽车职业技术学院汽车工程系,合肥230601 [2]合肥工业大学汽车与交通工程学院,合肥230000

出　　处：《海南热带海洋学院学报》2024年第2期69-76,共8页Journal of Hainan Tropical Ocean University

基　　金：安徽省高等学校重点科研项目(2022AH053138)。

摘　　要：局部定位节点信息与锚节点信息存在时间上的误差,导致相同节点坐标位置上的信息无法统一,进而对车辆路径规划轨迹造成严重偏差,为解决该问题,提出了一种无人驾驶牵引车自主巡航路径规划方法。通过蒙特卡罗节点定位和多区域分布传感器采集的定位信息,量化坐标参量;然后将蒙特卡罗定位算法引入参量优化过程中,通过路径规划定位点距离测算,计算有效定位区域内节点与目标锚节点之间的位置距离;构建路径巡航规划参量优化模型,求解节点位置数据,输出最优的无人驾驶牵引车自主巡航路径。仿真结果表明,路径规划精准,指标值符合测试标准,路径规划节点覆盖率较高。The temporal error of the local positioning node information and the anchor node information results in that the information on the same node coordinate position cannot be unified,which causes serious vehicle path planning trajectory deviation.Therefore,an autonomous cruise path planning method for driverless tractor was proposed.Through the Monte Carlo node positioning of the driverless tractor and the positioning information collected by multi⁃area distributed sensors,the coordi⁃nate parameters were quantified.Then Monte Carlo localization algorithm was introduced into parameter optimization,and the location distance between the node and the target anchor node in the effective localization area was obtained by measuring the distance of the location points in the path planning.After the optimization model of route cruise planning parameters was constructed and the node position data was solved,the optimal autonomous cruise path of the driverless tractor was outputted.The simulation results show that the path planning is accurate,the index values meet the test standards,and the path plan⁃ning node coverage is high.

关 键 词：蒙特卡罗定位算法 无人驾驶 牵引车 自主巡航 路径规划 

分 类 号：TN911[电子电信—通信与信息系统]