基于五次多项式规划和模糊LQR控制的平行泊车研究  

Research on Parallel Parking Using Fifth-Degree Polynomial Planning and Fuzzy LQR Control

作　　者：张成涛[1] 王瑞敏 张方 赵晓卓 骆远鹏 黎俊宏 ZHANG Chengtao;WANG Ruimin;ZHANG Fang;ZHAO Xiaozhuo;LUO Yuanpeng;LI Junhong(School of Mechanical and Automotive Engineering,Guangxi University of Science and Technology,Liuzhou 545616,Guangxi,China)

机构地区：[1]广西科技大学机械与汽车工程学院,广西柳州545616

出　　处：《汽车工程学报》2025年第2期211-223,共13页Chinese Journal of Automotive Engineering

基　　金：中央引导地方科技发展资金项目(桂科ZY23055014);广西科技重大专项(桂科AA22068100);广西科技计划项目(桂科AB21220052)。

摘　　要：针对自动泊车路径规划中曲率不连续的问题,基于对车辆运动学的分析,将圆弧-直线-圆弧规划方法与泊车任务的逆过程相结合,采用五次多项式优化方法来规划泊车路径,得到曲率连续的紧凑泊车轨迹。为了提高泊车跟踪精度,利用模糊控制方法对基于运动学模型的离散LQR跟踪控制器进行改进。为验证算法的有效性进行了仿真与试验验证,在Simulink/CarSim协同仿真中,其最大跟踪误差为0.027 m,平均跟踪误差为0.013 m。在实车试验中,最大跟踪误差为0.07 m,平均跟踪误差为0.029 m。相较于LQR跟踪控制器,FUZZY-LQR跟踪控制器的平均跟踪误差降低了33%,改善了自动泊车路径跟踪效果。To address the issue of discontinuous curvature in autonomous parking path planning,this paper analyzes vehicle kinematics,and combines the arc-line-arc planning method with the reverse parking process.A fifth-degree polynomial optimization approach is employed to generate a compact parking trajectory with continuous curvature.To enhance parking tracking accuracy,the discrete LQR tracking controller based on the kinematic model is improved using fuzzy control methods.Simulations and experimental validations are conducted to verify the effectiveness of the algorithm.In the Simulink/CarSim co-simulation,the maximum tracking error is 0.027 m,and the average tracking error is 0.013 m.In real-vehicle experiments,the maximum tracking error is 0.07 m,and the average tracking error is 0.029 m.Compared to the LQR tracking controller,the FUZZY-LQR tracking controller reduces the average tracking error by 33%,improving the autonomous parking path tracking performance.

关 键 词：自动泊车 路径规划 五次多项式优化 模糊控制 LQR 

分 类 号：U491.7[交通运输工程—交通运输规划与管理]