摩擦极限下自动驾驶汽车的路径跟踪

Vincent A. Laurense, Jonathan Y. Goh, J. C. Gerdes
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引用次数: 68

摘要

使用所有可用轮胎力的能力对公路车辆进行紧急机动和比赛至关重要。当转向不足的车辆在轮胎与路面摩擦的极限下转弯时,前轮饱和,转向作为路径跟踪的控制输入就失去了作用。一辆自动驾驶汽车的实验数据表明,为了在摩擦极限下通过转向进行路径跟踪,需要知道的摩擦值在大约2%以内。这一要求超出了现有实时摩擦估计算法的能力。通过对专业赛车手的数据采集,提出了一种新的控制框架,该框架采用基于滑移角的控制策略,使前轮胎保持在获得最大轮胎力的滑移角上,并采用纵向速度控制进行路径跟踪。该方法对摩擦估计精度的要求明显降低。提出了一种控制器来探索这一概念,实验结果表明,在没有先验摩擦信息的情况下,成功地跟踪了摩擦极限处的圆路径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Path-tracking for autonomous vehicles at the limit of friction
The ability to use all of the available tire force is essential to road vehicles for emergency maneuvers and racing. As the front tires of an understeering vehicle saturate while cornering at the limit of tire-road friction, steering is lost as a control input for path-tracking. Experimental data from an autonomous vehicle show that for path-tracking at the limit of friction through steering the value of friction needs to be known to within approximately 2%. This requirement exceeds the capabilities of existing real-time friction estimation algorithms. Data collected with a professional race car driver inspire a novel control framework, with a slip angle-based control strategy of maintaining the front tires at the slip angle for which maximum tire force is attained, and longitudinal speed control for path-tracking. This approach has significantly less demanding requirements on the accuracy of friction estimation. A controller is presented to explore this concept, and experimental results demonstrate successful tracking of a circular path at the friction limit without a priori friction information.
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