Cluster-wise cooperative eco-approach and departure application along signalized arterials

Abstract

In recent years, the Eco-Approach and Departure (EAD) application has been widely studied, which utilizes Signal Phase and Timing (SPaT) information to allow connected and automated vehicles (CAVs) to approach and depart from a signalized intersection in an energy-efficient manner. However, most existing work have studied the EAD application from an ego-vehicle perspective (Ego-EAD), where a single vehicle makes use of Infrastructure-to-Vehicle (I2V) communication, without considering the effect on traffic throughput. To date, relatively limited research about EAD application takes into account cooperation among vehicles at intersections via Vehicle-to-Vehicle (V2V) communication, aiming to benefit not only one vehicle but the entire traffic flow. In this study, we develop a cluster-wise cooperative EAD (Coop-EAD) system to further reduce energy consumption while increasing traffic throughput, compared to existing Ego-EAD applications. Instead of considering CAVs traveling through signalized intersections one at a time, our approach strategically coordinates CAVs' maneuvers to form clusters with the proposed methodologies: initial vehicle clustering, intra-cluster sequence optimization, and cluster formation control. The EAD algorithm is then applied to the cluster leader, and CAVs in the cluster can conduct EAD maneuvers by following the dynamics of the cluster leader. A comprehensive simulation study shows that, compared to an Ego-EAD system, the proposed Coop-EAD system achieves 50% increase on traffic throughput, 11% reduction on energy consumption, and up to 20% reduction on pollutant emissions, respectively.