Heterogeneous Traffic Flow Dynamics under Various Penetration Rates of Connected and Autonomous Vehicle

Abstract

This study aims to analyze the impact of connected and autonomous vehicles (CAVs) on traffic flow under various penetration rates. Based on a recently proposed heterogeneous flow model, the mixed traffic flow with both conventional vehicles and CAVs was simulated and studied. Acceleration rate and velocity distributions of the mixed traffic flow were presented to show the evolution of mixed traffic flow dynamics with the increase in CAV penetration rate within the mixed flow. Spatiotemporal diagrams of mixed traffic flow were presented to show the effect of CAVs on damping the stop-and-go traffic flow. Results show that with the increase in CAV penetration rate, the portion of smooth driving is increased. Velocity difference between vehicles is decreased and traffic flow is greatly smoothed. Stop-and-go traffic will be greatly eased when CAV penetration rate reaches a rate of 40%∼50%. More cautious following strategy of the CAV would contribute to a greater benefit on traffic safety. This work provides some insights into the impact of the CAV on traffic flow and sheds light on how would the mixed traffic flow dynamics evolve with the gradual adoption of CAV under current traffic system.