An Expert Fuzzy Controller for Vehicle Lateral Control

Jing Yang, N. Zheng
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引用次数: 28

Abstract

Vehicle lateral control is a challenging problem in areas of intelligent transportation systems (ITS) and automatic control for autonomous vehicles. Most of solutions for lateral control proposed, such as PID, simple fuzzy logic control and H- infinity, are proved accurate and effective only in simple driving task, such as lane changing, lane following and small curvature crossing turning action. For big curvature crossing turning action, the solutions mentioned above haven't dealt with In this paper, we propose an expert fuzzy controller, which is based on a 2 degree of freedom (2DOF) vehicle lateral dynamic model, to solve the problem both in simple driving task and big curvature crossing turning action. The traditional 2DOF analytic model is used in lane changing, lane following and small curvature crossing turning actions, while an experimental model is used in big curvature crossing turning That is because the traditional 2DOF analytic model is set up based on the hypothesis that the steering angle of front wheel is small. The experimental model is proved accurate and effective in the realistic driving experiments. In addition, it is proved that the expert fuzzy controller is effective to solve the lateral control problem in complicated driving tasks, such as lane changing, lane following, small and big curvature crossing turning actions, in both simulations and experiments.
车辆横向控制的专家模糊控制器
车辆横向控制是智能交通系统(ITS)和自动驾驶汽车自动控制领域的一个具有挑战性的问题。大多数横向控制方法,如PID、简单模糊逻辑控制和H-∞等,仅在变道、跟道和小曲率转弯等简单的驾驶任务中被证明是准确有效的。对于大曲率过弯问题,本文提出了一种基于2自由度车辆横向动力学模型的专家模糊控制器,既能解决简单驾驶任务,又能解决大曲率过弯问题。传统的2DOF解析模型用于变道、跟道和小曲率过弯动作,而大曲率过弯动作则采用实验模型。这是因为传统的2DOF解析模型是建立在前轮转向角较小的假设基础上的。实际驾驶试验证明了该模型的准确性和有效性。仿真和实验结果表明,专家模糊控制器能够有效地解决变道、跟道、小曲率和大曲率转弯等复杂驾驶任务中的横向控制问题。
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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