Eco Driving

Eco-driving aims to optimize vehicle speed and acceleration to minimize fuel consumption and emissions, thereby improving both environmental sustainability and energy efficiency. Current research heavily utilizes reinforcement learning (RL), often in conjunction with deep neural networks, to develop sophisticated control strategies for both autonomous and human-driven vehicles, considering factors like traffic flow, intersection type, and vehicle-to-everything communication. These advancements are impacting transportation systems through improved energy management in hybrid and electric vehicles, reduced emissions at signalized and unsignalized intersections, and the development of more effective driver assistance systems.