Abstract

Modeling the impact of the cooperative driving strategy adopted by Cooperative Adaptive Cruise Control (CACC) vehicles on the mixed traffic flow would be a challenge. It requires to figure out the behaviors of CACC vehicles during the formation and disengagement of CACC strings when the manually driven vehicles are mixed in the traffic flow. It also needs to depict the behaviors of manually driven vehicles under the influence of CACC operation strategy that are intended to enhance the CACC string. To deal with these problems, we propose a four-lane cellular automata traffic modeling framework to simulate the interaction between CACC vehicles and manually driven vehicles. The longitudinal position updating rules for CACC and ACC are based on the car-following rules presented by PATH laboratory of University of California, Berkeley. And three types of cooperative driving strategies are presented, which are reflected in the lane-changing rules, i.e., the baseline lane-changing rules, the promoting string strategy and the managed lane strategy. The corresponding impact of cooperative driving strategies on mixed four-lane traffic flow is investigated. The numerical results show that the presented cooperative driving strategies are effective to enable CACC to be assembled into strings. And the increase of CACC penetration could effectively alleviate traffic congestion and improve traffic capacity and stability. The results indicate that the mixed traffic flow shows different properties in terms of capacity and traffic congestion when different cooperative driving strategies are adopted.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call