The development of autonomous vehicles has shown great potential to enhance the
efficiency and safety of transportation systems. However, the decision-making issue in …

Proper functioning of connected and automated vehicles (CAVs) is crucial for the safety and
efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous …

In the future, mixed traffic flow will include two types of vehicles: connected autonomous
vehicles (CAVs) and human-driven vehicles (HDVs). CAVs emerge as new solutions to …

The recent proliferation of the research on multi-agent deep reinforcement learning (MDRL)
offers an encouraging way to coordinate multiple connected and automated vehicles (CAVs) …

Intersections are key nodes and also bottlenecks of urban road networks, so improving the
traffic efficiency at intersections is beneficial to improving overall traffic throughput and …

With the advent of machine learning, several autonomous driving tasks have become easier
to accomplish. Nonetheless, the proliferation of autonomous vehicles in urban traffic …

Autonomous Intersection Management (AIM) systems present a new paradigm for conflict-
free cooperation of connected autonomous vehicles (CAVs) at road intersections, the aim of …

Despite rapid advances in vehicle intelligence and connectivity, there is still a significant
period in mixed traffic where connected, automated vehicles and human-driven vehicles …

Abstract The application of Deep Reinforcement Learning (DRL) has significantly impacted
the development of autonomous driving technology in the field of intelligent transportation …

Autonomous driving has attracted significant research interests in the past two decades as it
offers many potential benefits, including releasing drivers from exhausting driving and …