  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 (SPaT) 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 work have studied the EAD
application from an ego-vehicle perspective (Ego-EAD) using
Vehicle-to-Infrastructure (V2I) communication, while relatively limited
research takes into account cooperation among vehicles at intersections via
Vehicle-to-Vehicle (V2V) communication. In this research, 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, intra-cluster 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 19.9% reduction
on pollutant emissions, and 50% increase on traffic throughput, respectively.
