Evaluation of a New Real-Life Traffic Management Using a Limited Number of Connected Autonomous Vehicles

Methodologies for managing traffic in real-time are evolved in a different direction with the development of Connected Autonomous Vehicles (CAVs). Most of the research uses a specific penetration rate of CAVs. The contribution of this study is to fill that gap by testing a new real-time traffic management method, named SWSCAV (utilization of shockwave-speed information and connected autonomous vehicles for traffic management in case of congestion or incident) in case of a traffic incident in an uninterrupted traffic flow environment with a very limited number of CAVs to improve conditions of the traffic flow conditions. By changing the lane and duration of the simulated incident and adjusting the arrival frequency of the CAVs and the position where the CAVs reduce their speeds, 189 different scenarios are tested. Mean flow, density, and speed values are selected as measures of effectiveness. These metrics are inspected both network-wide and locally using a Simulation of the Urban Mobility (SUMO) environment. A maximum of 12 CAVs are used. The results show that introducing SWSCAV with a limited number of CAVs means speed and flow values can increase up to 20.35% and 2.45%, respectively. Additionally, a decrease in mean density up to 32.54% can also be observed with this management approach. Density heat maps are used to inspect the influence of the incident.