Proactive Eco-Driving Control of an Autonomous Electric Vehicle in Presence of Signalized Intersections and Preceding Vehicles

The study proposes a dynamic proactive predictive cruise control eco-driving (eco-PPCC) framework for controlling the speed of an Autonomous Electric Vehicle (AEV) approaching a signalized intersection in the presence of a preceding vehicle. By utilizing the preceding vehicle's data, the framework optimizes the AEV's speed profile, achieving significant reductions in energy consumption. The study compares the proposed eco-PPCC algorithm to the conventional Gipps and eco-PCC models, and real-world measurements are taken to study practical scenarios. The results show that the proposed framework outperforms conventional methods by significantly reducing unnecessary stops at intersections, speed fluctuations, and energy consumption.