Eco-Approach and Departure along Signalized Corridors Considering Powertrain Characteristics

With the emergence of connected and automated vehicles (CAVs), numerous dynamic eco-driving strategies have been developed all over the world. The Eco-Approach and Departure (EAD) application is considered to be a promising solution to the relief of transportation activity-related pressure on energy and environment. Unlike most of existing EAD strategies that utilize signal phase and timing (SPaT) information on an intersection basis, we propose a computationally efficient algorithm for EAD along signalized corridors (EADSC), which can take advantage of SPaT information of all the intersections along the corridor as a whole, and can determine the optimal (in terms of fuel efficiency) speed trajectories with the consideration of the host vehicle’s powertrain characteristics. Both the numerical study and real-world field implementation indicate that the proposed EADSC system shows great promise in fuel savings (e.g., ranging from 12% to 28%) without compromising on mobility, compared to the baseline driving strategy without SPaT knowledge and other representative EAD strategies. We also discuss some practical issues when deploying the proposed system in the real-world, such as unavailability of complete knowledge on the background signal timing plan in current SPaT messages, and handling of interactions from other traffic (e.g., cut-ins).