Speed-Adaptive Model-Free Path-Tracking Control for Autonomous Vehicles: Analysis and Design

Marcos Moreno-Gonzalez, Antonio Artuñedo, J. Villagrá, C. Join, M. Fliess
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引用次数: 4

Abstract

One of the challenges of autonomous driving is to increase the number of situations in which an intelligent vehicle can continue to operate without human intervention. This requires path-tracking control to keep the vehicle stable while following the road, regardless of the shape of the road or the longitudinal speed at which it is moving. In this work, a control strategy framed in the Model-Free Control paradigm is presented to control the lateral vehicle dynamics in a decoupled control architecture. This strategy is designed to guide the vehicle through trajectories with diverse dynamic constraints and over a wide speed range. A design method for this control strategy is proposed, and metrics for trajectory tracking quality, system stability, and passenger comfort are applied to evaluate the controller’s performance. Finally, simulation and real-world tests show that the developed strategy is able to track realistic trajectories with a high degree of accuracy, safety, and comfort.
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自动驾驶汽车无模型自适应路径跟踪控制:分析与设计
自动驾驶面临的挑战之一是增加智能汽车在没有人为干预的情况下继续运行的情况。这需要路径跟踪控制来保持车辆在跟随道路时的稳定,无论道路的形状或其移动的纵向速度如何。在这项工作中,提出了一种基于无模型控制范式的控制策略,在解耦控制体系结构中控制车辆的横向动力学。该策略旨在引导车辆通过具有多种动态约束和宽速度范围的轨迹。提出了该控制策略的设计方法,并应用轨迹跟踪质量、系统稳定性和乘客舒适度等指标来评价控制器的性能。最后,仿真和实际测试表明,所开发的策略能够以高度的准确性、安全性和舒适性跟踪真实轨迹。
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