基于混行跟驰仿真的CAV专用进口道动态设置方法

Signalized intersections are critical for the safety and efficiency of urban traffic systems. With the proposal of the new national infrastructure strategy and the continuous development of vehicle-road coordination techniques, the layout of connected and automated vehicle (CAV) entrance lanes for intersections is beneficial to improving capacity and reducing delay, and promoting the efficiency and safety of urban transportation systems. However, the use of CAVs influences the car-following characteristics, which are different from those of traditional vehicles. In this study, cooperative adaptive cruise control and General Motor models were established to simulate the car-following behavior of connected and nonconnected vehicles, respectively. The operational characteristics of a mixed traffic flow under different driving conditions at signalized intersections were then simulated using the models. The dynamic layout conditions for the CAV entrance lane under different conditions were proposed to improve capacity and minimize delay and fuel consumption, considering the ratio of CAVs, number of entrance lanes, traffic volume, and signal timing scheme. The numerical simulation results indicate that the proposed method improves traffic efficiency and reduces delay and fuel consumption at signalized intersections. A feasible approach for designing CAV entrance lanes at signalized intersections in intelligent network environments was proposed in this study. Moreover, this study can serve as a reference for related research on vehicle-road coordination systems.