Cluster-Wise Cooperative Eco-Approach and Departure Application for Connected and Automated Vehicles Along Signalized Arterials

In recent years, various versions of the eco-approach and departure (EAD) application have been developed and evaluated. This application utilizes signal phase and timing information to allow connected and automated vehicles (CAVs) to approach and depart from a signalized intersection in an energy-efficient manner. To date, most existing works have studied the EAD application from an ego-vehicle perspective (Ego-EAD) using vehicle-to-infrastructure communication, while relatively limited research takes into account cooperation among vehicles at intersections via vehicle-to-vehicle communication. In this paper, we developed a cluster-wise cooperative EAD (Coop-EAD) application for CAVs to further reduce energy consumption 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 using various operating modes: initial vehicle clustering, intracluster sequence optimization, and cluster formation control. The novel Coop-EAD algorithm is applied to the cluster leader, and CAVs in the cluster follow the cluster leader to conduct EAD maneuvers. A preliminary simulation study with a given scenario shows that, compared to an Ego-EAD application, the proposed Coop-EAD application achieves 11% reduction on energy consumption, up to 18% reduction on pollutant emissions, and 50% increase on traffic throughput, respectively.