Mechanism of Non-recurring Congestion Evolution Under Mixed Traffic Flow with Connected and Autonomous Vehicles

This paper investigates the interference between connected and autonomous vehicles (CAVs) and the traditional vehicles in mixed traffic flow, and proposed a model to describe the evolution of the non-recurring congestions in the mixed traffic flow. The model is developed based on the traditional traffic flow statistical theory model and the first-order continuous medium model, and introduced the intelligent driver model (IDM) and cooperative adaptive cruise control (CACC). The study uses the roadway section from Huatao Interchange to Banan Interchange in Chongqing City as a case study to examine the congestion evolution under different permeability (Pc ) of CAVs in the traffic flow. The results show that higher penetration rate of CAVs relates to more significant improvement of the flow, occupancy, and speed of the mixed traffic flow. However, the improvement of congestion dissipation by CAVs is more obvious when Pc ≥ 0.2 . When Pc ≤ 0.8, the duration of the congestion dissipation state with interference measure is approximately 50% of that without interference measure. When Pc = 1.0, the traffic capacity of CAVs is 2.34 times of that in traffic flow with only traditional vehicles. The traffic congestion evaluation indexes are calculated under noninterference and interference measures and compared with the simulation results. The maximum relative error is within 5.38 %, which verified the model's accuracy. The research results provide important references for traffic congestion evaluations. © 2022 Science Press. All rights reserved.