Bifurcation and phase transitions in heterogeneous non-lane-discipline-based car-following model integrating cooperative feedback control under automated and human-driven vehicles environment
Guanghan Peng, Kunning Wu, Huili Tan
Abstract
Automated vehicles (AVs) equipped with adaptive cruise control (ACC) possess different driving performances from human-driven vehicles (HDVs). AVs will have an unusual impact on the traffic flow, especially in non-lane-discipline-based (NLD) environment. Therefore, we create a heterogeneous NLD car-following model (HNLD-CFM) integrating cooperative feedback control under AVs and HDVs environment. The velocity differences between two preceding vehicles and the current vehicle are adopted for the cooperative feedback control signal. The stability condition of the HNLD-CFM is inferred through control theory, which is closely related to the proportion of AVs, lateral separation of vehicles and control signal. Moreover, bifurcation phenomena are been investigated via theory analysis and simulation. Furthermore, numerical simulation clarifies that traffic congestion can be effectively suppressed and energy consumption is reduced by increasing the proportion of AVs and lateral separation of vehicles, besides a control signal.