中文摘要：

驾驶员方向控制模型在人-车-路闭环系统仿真、驾驶员辅助系统开发和智能汽车控制中具有重要作用。在假设驾驶员具有汽车轨迹预测能力的基础上,提出一类基于轨迹预测的驾驶员方向控制模型。分别假定汽车在将来一段时间内保持恒定的横摆角速度或横摆角加速度,并结合汽车状态参数预测汽车的行驶轨迹,采用期望式、增量式以及期望式与增量式集成的转角决策方法建立5种不同的驾驶员模型。在ve DYNA/Simulink联合仿真平台上对各驾驶员模型进行仿真试验,结果表明,增量式驾驶员模型表现出良好的路径跟踪精度和很强的鲁棒性,期望式模型的转向操纵更加平滑,而集成式模型则具备综合优势。在ve DYNA/Labview硬件在环实时试验台架上对所提出的驾驶员模型进行模拟试验,所得结论与仿真基本一致。

英文摘要：

Driver directional control model is needed in the simulation of driver-vehicle-road closed-loop system, the development of driver assistance systems and the control of intelligent vehicle. Based on the assumption that the driver has the ability to predict the trajectory of the vehicle, a class of driver directional control model based on trajectory prediction is proposed. According to the assumptions that the vehicle keep the yaw rate or yaw acceleration constant in the near future and combining vehicle state parameters, the vehicle motion trajectory is calculated. Five different driver models are formulated according to multiple decision methods of steering angle, consisting of the desired-type, the incremental-type and the integrated-type. Simulation test of the proposed driver models is carried out on the ve DYNA/Simulink co-simulation platform, the results show that the incremental-type driver model exhibits good path tracking accuracy and robustness, the desired-type model achieves a better smoothness of steering, and the integrated-type model obtain comprehensive advantages. The proposed driver models are experimentally validated on a ve DYNA/Labview-based hardware-in-the-loop real-time test bench, the conclusions are consistent with the simulation conclusions.