Research on Lateral Tracking Control of Low Speed Intelligent Vehicle Using Dynamic Path Preview Model
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摘要: 采用速度自适应的动态预瞄距离是提高智能车侧向跟踪控制效果的有效办法。针对目前基本采用基于当前车速的预瞄距离自适应策略,提出一种结合规划路径和规划速度信息的动态预瞄距离跟踪控制算法以提高智能车在低速侧向跟踪控制的精确性。本文以几何学纯跟踪算法为基础,推导了前行和倒车时的侧向跟踪控制律;依据实时规划的路径和速度信息,设计了预瞄距离动态调整方法,最终获取具有速度自适应性的前视距离-车辆前轮转角关系。最后,在CarSim-MATLAB/Simulink联合仿真环境下验证了算法的有效性和准确性,并通过实车测试,验证了所提出的方法较基于动力学模型的LQR算法具有更低计算消耗和更高跟踪精度。Abstract: Speed adaptive dynamic preview distance is an effective way to improve the lateral tracking control effect of intelligent vehicle, and as for the problem of using current vehicle speed for the preview distance, a dynamic preview distance tracking control algorithm combining planned path and planned speed information is proposed to improve the accuracy of path tracking at low speed. Based on the pure pursue algorithm, the lateral tracking control laws of moving forward and reversing are derived. According to the real-time planned path and speed information, a dynamic adjustment method of preview distance was designed, and the relationship between the preview distance and the steering angle with speed adaptability was thereby obtained. Finally, the effectiveness and accuracy of the proposed algorithm were verified in CarSim-MATLAB/Simulink co-simulation environment, and a real vehicle test was performed, indicating that the proposed algorithm has lower computational consumption and higher tracking accuracy than the LQR algorithm based on dynamics model.
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表 1 实车测试车辆参数
Table 1. Tested vehicle parameters
参数 数值 智能汽车质量/kg 1 830 质心到前轴的距离/m 1.276 质心到后轴的距离/m 1.589 转动惯量/(kg·m2) 3 710.41 前轮侧偏刚度/(N·rad-1) -150 000 后轮侧偏刚度/(N·rad-1) -150 000 转向系角传动比isw 15.9 -
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