Linear model predictive control for lane keeping and obstacle avoidance on low curvature roads

Valerio Turri, Ashwin Carvalho, H. E. Tseng, K. Johansson, F. Borrelli
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引用次数: 111

Abstract

This paper presents a control architecture based on a linear MPC formulation that addresses the lane keeping and obstacle avoidance problems for a passenger car driving on low curvature roads. The proposed control design decouples the longitudinal and lateral dynamics in two successive stages. First, plausible braking or throttle profiles are defined over the prediction horizon. Then, based on these profiles, linear time-varying models of the vehicle lateral dynamics are derived and used to formulate the associated linear MPC problems. The solutions of the optimization problems are used to determine for every time step, the optimal braking or throttle command and the corresponding steering angle command. Simulations show the ability of the controller to overcome multiple obstacles and keep the lane. Experimental results on an autonomous passenger vehicle driving on slippery roads show the effectiveness of the approach.
低曲率道路车道保持与避障的线性模型预测控制
本文提出了一种基于线性MPC公式的控制体系结构,用于解决乘用车在低曲率道路上行驶时的车道保持和避障问题。所提出的控制设计在两个连续的阶段解耦了纵向和横向动力学。首先,在预测范围内定义合理的制动或油门配置。然后,在此基础上推导了车辆横向动力学的线性时变模型,并将其用于求解相关的线性MPC问题。利用优化问题的解,确定每个时间步长的最优制动或油门指令以及相应的转向角指令。仿真结果表明,该控制器具有克服多个障碍物并保持车道畅通的能力。在湿滑路面上的自动驾驶乘用车试验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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