The development of connected autonomous vehicles (CAVs) facilitates the enhancement of
traffic efficiency in complicated scenarios. Difficulties remain unsolved in developing an …

Reinforcement learning (RL) can free automated vehicles (AVs) from the car-following
constraints and provide more possible explorations for mixed behavior. This study uses …

This paper focuses on cooperative driving strategies at on-ramps and comprehensively
compares the performance of five representative strategies. The simulation results show that …

In order to effectively improve the path‐finding capability of a multirobot system in a
decentralized control approach, a dynamic motion planning model based on graph neural …

Intersection management of Connected Autonomous Vehicles (CAVs) has the potential to
significantly improve safety and mobility. While numerous intersection management designs …

Abstract In Yangtze River traffic management, to manage ship sequencing and scheduling
effectively and efficiently in restricted waterways has long been a challenging issue. This …

The control architecture for Connected and Automated Vehicles (CAVs) proposed in this
work combines three features: Scalable, Distributed, and Reconfigurable. The term Scalable …

Connected and Automated Vehicles (CAVs) are highly expected to improve traffic
throughput and safety at road intersections, single-track lanes, and construction zones …

The development of connected autonomous vehicles (CAVs) facilitates the enhancement of
traffic efficiency in complicated scenarios. In unsignalized roundabout scenarios, difficulties …

Waiting in a long queue at traffic lights not only wastes valuable time but also pollutes the
environment. With the advances in autonomous vehicles and 5G networks, the previous …