In vehicle longitudinal control, improved comfort and reduced operation workload for human drivers are achieved with the ACC (Adaptive Cruise Control), which still requires the driver to maintain full attention on monitoring, meanwhile, the risk of distraction and fatigue rises resulting from the long-term supervising task, which has a strong impact on the successful takeover. The key point to make full use of ACC advantages and make up human’s weakness on supervising task is the reasonable arrangement of control time of ACC and human driver. In this paper, an MPC (Model Predictive Control) based optimized switching strategy of longitudinal driving authority transition is proposed, which aims to provide proper advice for human drivers to handover and takeover control authority, through minimizing the overall index consisted of the operation workload, fuel consumption, takeover risk and tracking errors. In addition, a new driver longitudinal model considering actual reaction time delay and insensitive distance perception of human drivers is proposed as well, which combines with ACC to constitute a typical switched control system called the switched driving model as the predictive model for MPC. The stable condition of the new driver longitudinal model is derived by using describing function method and a sufficient condition to ensure steady switched system is given by using the Lyapunov method and LMI approach. The results of simulator experiments show that the new driver model describes the car-following behavior of real human driver better. What’s more, the simulation results demonstrate that the performance index of switched driving is smaller than the human driving and ACC driving only, and the optimization time is short enough to meet the requirement of engineering practice.

在车辆纵向控制中，借助ACC（自适应巡航控制系统）可以提高驾驶员的舒适度并减少操作工作量，这仍然要求驾驶员全神贯注地进行监控，同时，长时间驾驶会分散注意力和疲劳风险监督任务，对成功接管有很大影响。充分利用ACC的优点，弥补人在监督任务上的弱点，关键在于合理安排ACC和驾驶员的控制时间。本文提出了一种基于MPC（模型预测控制）的纵向驾驶权转移优化切换策略，旨在为驾驶员提供适当的建议，以实现交接和接管控制权，通过最小化总体指标，包括运营工作量，燃油消耗，接管风险和跟踪错误。此外，还提出了一种考虑驾驶员实际反应时间延迟和不敏感距离感知的驾驶员纵向模型，该模型与ACC相结合，构成了一个典型的开关控制系统，称为MPC的预测模型。利用描述函数法推导了新驾驶员纵向模型的稳定条件，并使用Lyapunov方法和LMI方法给出了确保稳定切换系统的充分条件。仿真实验结果表明，新的驾驶员模型较好地描述了真实驾驶员的跟车行为。更重要的是，