基于改进车辆运动学模型的自动驾驶车辆横向和纵向轨迹耦合跟踪控制

Sijie Li, Zhanbo Sun, Yafei Liu, Ang Ji, Shuaifei Zhang, Linbin Chen
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引用次数: 0

摘要

摘要为了提高自动驾驶汽车轨迹跟踪的精度和稳定性,提出了一种基于模型预测控制(MPC)的横向和纵向耦合轨迹跟踪控制算法。基于修正的车辆运动学模型,以转向角和纵向速度为控制变量,开发了MPC耦合控制器。通过CarSim和MATLAB/Simulink联合仿真实验验证了改进后的车辆模型和耦合MPC控制器。仿真结果表明,在平均计算时间增加12%的代价下,与基于经典运动学模型的基准耦合横向和纵向MPC控制器相比,所提出的耦合MPC控制器的跟踪误差减少了约48%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coupled lateral and longitudinal trajectory tracking control with a modified vehicle kinematics model for autonomous vehicles
Abstract The paper proposes a coupled lateral and longitudinal trajectory tracking control algorithm based on model predictive control (MPC) to enhance the precision and stability of trajectory tracking of autonomous vehicles. The coupled MPC controller is developed based on a modified vehicle kinematics model, which simultaneously takes the steering angle and the longitudinal speed as control variables. The modified vehicle model and the coupled MPC controller are verified by CarSim and MATLAB/Simulink co-simulation experiments. Simulation results demonstrate that, at the cost of 12 percent increase in average computational time, the proposed coupled MPC controller leads to an approximate 48 percent reduction in tracking error compared to the benchmarking coupled lateral and longitudinal MPC controller based on the classic kinematics model.
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