Autonomous driving technology pledges safety, convenience, and energy efficiency. Its
challenges include the unknown intentions of other road users: communication between …

Urban transport contributes more than a quarter of the global greenhouse gas emissionns
that drive climate change; it also produces significant air pollution emissions. Furthermore …

This research proposed an eco-driving system for an isolated signalized intersection under
partially Connected and Automated Vehicles (CAV) environment. This system prioritizes …

Traffic signals typically introduce vehicle stops along a trip and thus increase vehicle fuel
consumption levels. In attempt to enhance vehicle fuel efficiency, eco-cooperative adaptive …

Energy consumption and driving safety of a vehicle are greatly influenced by the driving
behaviors of the vehicle in front (also termed the preceding vehicle). Inappropriate …

This study proposes autonomous eco-driving strategies for a traffic environment with limited
information available based on three popular Reinforcement Learning (RL) algorithms for …

This paper proposes a real-time dynamic predictive cruise control (PCC) system to minimize
the energy consumption for electric vehicles (EVs) under integrated traffic situations with …

The connected vehicle eco-approach and departure (EAD) application for signalized
intersections has been widely studied and is deemed to be effective in terms of reducing …

Electric vehicles (EVs) have great potential to reduce transportation-related fossil fuel
consumption as well as pollutant and greenhouse gas (GHG) emissions, due to their use of …

Connected and automated vehicles (CAVs) offer promising prospects for the future of
transportation. However, the longstanding dominance of human-driven vehicles (HDVs) in …