Car-Following Model and Stability Analysis for Connected Heterogeneous Vehicle Groups

The intelligent connected driving system presents the coexistence development trend of Connected Autonomous Vehicles (CAV) and Human-driven Vehicles (HV), and new road service function and traffic behavior characteristics have emerged. The establishment of car-following model for connected heterogeneous vehicle groups can help to understand its car-following characteristics and improve its stability. Considering the optimal velocity and optimal velocity changes with memory based on front and rear car-head spacing, the velocity difference and acceleration difference of multiple front vehicles, a car-following model named Multiple Front and Rear Optimal Velocity Changes with Memory (MFROVCM) which is suitable for the interactive penetration of heterogeneous vehicle groups with CAV and HV is constructed. The stability analysis of the model shows: Compared with OVCM model, the unstable area is reduced by 53.17%; Compared with BL-OVCM model, the unstable area is reduced by 15.44%, and the stability of MFROVCM model is better than other comparison models. The simulation results show that under the same disturbance conditions, MFROVCM model has better vehicle groups stabilization performance. With the increase of CAV permeability, the fluctuation amplitude of overall vehicle groups velocity decreases, and the time to restore stability gradually decreases. The model can be applied to the car-following simulation of CAV and HV, and provides a theoretical basis and model basis for the traffic control strategy of connected heterogeneous vehicle groups.