汽车方向控制驾驶员模型

Driver Model of Steering Direction Control for Automobiles

建立合适的汽车方向控制驾驶员模型是人-车-路闭环系统最重要的环节之一.目前在传递函数、最优控制的基础上建立了补偿模型、预瞄补偿跟踪模型、预瞄最优曲率跟随模型等,但由于驾驶员驾驶特性的非线性、时变性等特征,上述模型很难模拟驾驶员实际操纵行为.考虑到驾驶员的操纵特性,运用智能控制理论,基于模糊控制、神经网络及这两者的结合,建立相应的驾驶员模型可以更加接近驾驶员实际的驾驶行为.

Creating a suitable driver model is one of the most important parts in the closed-loop system of driver-vehicleroad. Several kinds of driver models have been created based on the traditional control theories such as transfer function, optimization control and the compensation control. But owing to the driver＇ s characteristics of nonlinear and time-variable, it＇s difficult for those proposed driver models to mimic drivers＇ action. While accounting for the inherent manual control characteristics and limitations of the mankind, the intelligent control methods have been applied in creating driver models based on the fuzzy control, neural networks control and fuzzy-neural networks control theory.