Intelligent driver model for curved roads in vehicle-infrastructure cooperation environment with consideration of preceding vehicles’ information

Radius of road curvature and the information of preceding vehicles have a significant influence on traffic flow in the vehicle-infrastructure cooperation environment. However, the existing car-following model is subjective in considering the type of preceding vehicles' information, and does not comprehensively consider the synergistic effect of road curvature radius and preceding vehicles' information. Therefore, in this study, an intelligent driver model for curved roads considering multi-preceding vehicles' information is established in the vehicle-infrastructure cooperation environment. Then, using the Lyapunov method to analyze the stability of the extended model, the linear stability condition is obtained, and the influence law of radius of road curvature and weight coefficient of the preceding vehicle on traffic flow is mastered. Finally, the theoretical analysis of the model is verified by numerical simulation experiments. The simulation results are consistent with the theoretical analysis, and both show that the stability of traffic flow increases with the increase of radius of road curvature and weight coefficient of the preceding vehicle. This shows that the extended model can not only accurately describe the car-following behavior of vehicles on a curved road in the vehicle-infrastructure cooperation environment but also stabilize the traffic flow and suppress traffic jams.