String Stable Control of Mixed Vehicle Platoon Time-delay System Considering Backward-looking Effects and Disturbances

In this paper, a hybrid platooning robust stability control method based on the Backward Predictive Multi-Vehicle Following Method (BLAMCFM) is proposed to address the problems that the following models of traditional human-driven vehicles (HDVs) do not take into account the personalized characteristics of real drivers and that it is difficult to achieve the stability of a hybrid vehicle platooning system with the vehicle platooning control method. Firstly, data from various vehicles in front and behind are used as inputs to the HDV. Subsequently, a hybrid platooning system consisting of a self-driving and connected vehicle (CAV) and an HDV is established, considering several unfavorable factors such as data dropout, communication delays, and external disturbances. Secondly, a string stability criterion for the hybrid platooning system is provided in the presence of disturbances and delays, and a stability controller is built based on the Lyapunov-Razumikhin stability theory. In conclusion, it is shown through simulation studies that drivers observing the behavior of multiple vehicles in front and behind them simultaneously can successfully stabilize the traffic flow, and the effectiveness of the controller is confirmed by illustrating the function of CAVs in reducing traffic oscillations.