基于学习的无人驾驶车辆模型预测路径跟踪控制研究

doi:10.19562/j.chinasae.qcgc.2024.07.007

Abstract

Abstract:

For the trade-off between prediction model accuracy and computational cost for path tracking control of autonomous vehicles， a learning-based model predictive control （LB-MPC） path tracking control strategy is proposed in this paper. A two-degree-of-freedom single-track vehicle dynamic model is established， and an in-depth analysis is conducted on its step response error with respect to variation in vehicle speed， pedal position， and front wheel steering angle compared to the IPG TruckMaker model. Methods for constructing error datasets and receding horizon updates are designed， and the Gaussian process regression （GPR） is employed to establish an error-fitting model for real-time error compensation and correction of the nominal single-track model. The error correction model is utilized as the prediction model， and a path tracking cost function is designed to formulate a quadratic programming optimization problem， proposing a learning-based model predictive path tracking control architecture. Through joint simulation using the IPG TruckMaker & Simulink platform and real vehicle experiments， the real-time performance and effectiveness of the proposed GPR error correction model and LB-MPC path tracking control strategy are verified. The results show that compared to the traditional model predictive control （MPC） path tracking control strategy， the proposed LB-MPC strategy reduces the average path tracking error by 23.64%.

Key words: path tracking, vehicle model error analysis, Gaussian process regression, model predictive control

Mo Han,Hongwen He,Man Shi,Wei Liu,Jianfei Cao,Jingda Wu. Research on Learning-Based Model Predictive Path Tracking Control for Autonomous Vehicles[J].Automotive Engineering, 2024, 46(7): 1197-1207.

Figures/Tables 20

References 25

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状态量含义	变量符号	变量表示	单位
横向车速	v_y	x₁	m/s
横摆角速度	ω	x₂	rad/s
大地坐标系横坐标位置	X	x₃	m
大地坐标系纵坐标位置	Y	x₄	m
大地坐标系航向角	θ	x₅	rad
控制量含义	变量符号	变量表示	单位
前轮转向角	δ_f	u	rad

参数	数值	参数	数值
整备质量/kg	10 850	迎风面积/m²	6.375
满载质量/kg	16 500	转向系统传动比	22.15
风阻系数	0.4	轮胎滚阻系数	0.009 8
车辆长度/m	10.5	轮距/m	2.078
转向盘转角限值/（°）	±800	轮胎侧偏刚度/ （N·rad^-1）	252 670
车轮滚动半径/m	0.5	z轴转动惯量/（kg·m²）	12 800

变量	模型	最大误差/ （m·s^-1）	平均误差/ （m·s^-1）	标准误差/ （m·s^-1）
Δv_y	误差补偿模型	8.96×10^-6	1.25×10^-6	2.73×10^-6
Δv_y	标称单轨模型	6.18×10^-3	3.05×10^-3	4.17×10^-3
Δω	误差补偿模型	4.27×10^-6	5.94×10^-7	1.19×10^-6
Δω	标称单轨模型	2.34×10^-3	1.09×10^-3	1.43×10^-3

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Research on Learning-Based Model Predictive Path Tracking Control for Autonomous Vehicles

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