Cooperative Incident Management in Mixed Traffic of CAVs and Human-Driven Vehicles

Traffic incident management in metropolitan areas is crucial for the recovery of road systems from accidents as well as the mobility and safety of the community. With the continuous improvement in computation and communication technologies, connected and automated vehicles (CAVs) exhibit the potential to relieve incident-induced traffic degradation. To understand the benefits of CAVs on traffic incidents, this paper models the impacts of CAVs with joint consideration of microscopic CAV driving behaviors and macroscopic traffic assignment in mixed traffic environment comprising both CAVs and human-driven vehicles (HDVs). Firstly, a generic traffic assignment model with mixed traffic is proposed to analyze the mixed traffic process from the macroscopic perspective. Then, we incorporate the traffic assignment model with bottleneck delays and incident effects from the microscopic perspective, to model the dynamic road system with incident effects in mixed traffic environment. Furthermore, cooperating with the mixed traffic assignment model, dynamic signal control policies are presented according to different incident severities, and the conditions for equilibrium existence, uniqueness and stability of the road system are derived. The analytical results indicate that road system stability with incident effects is closely related to the incident severity, signal control policy as well as penetration rate and spatial distribution of CAVs. Finally, simulation results are conducted to demonstrate the effectiveness of our proposed incident management policy in improving the recovery rate and system stability of road networks.

Automated summary

This paper models the impacts of connected and automated vehicles (CAVs) on traffic incidents by considering both microscopic CAV driving behaviors and macroscopic traffic assignment. The results indicate that the stability of the road system with incident effects is closely related to the incident severity, signal control policy, penetration rate, and spatial distribution of CAVs.