Efficient traffic control can alleviate traffic congestion, reduce fuel consumption, and improve
traffic safety. With the development of communication and automation technologies, regular …

Tackling traffic signal control through multi-agent reinforcement learning is a widely-
employed approach. However, current state-of-the-art models have drawbacks: intersections …

During disasters, swiftly and efficiently evacuating populations in hazardous situations is
crucial to minimize losses. This study proposes a novel framework to address dynamic …

The smart factory leads to a strong digitalization of industrial processes and continuous
communication between the systems integrated into the production, storage, and supply …

Current literature on joint optimization of intersection signal timing and connected automated
vehicle (CAV) trajectory mostly focuses on vehicular movements paying no or little attention …

Roadside sensing units'(RSUs) perception capability may be substantially impaired by
occlusion issue even they work cooperatively. However, the joint influence of static and …

With the introduction of connected and automated vehicles (CAVs), the integrated control of
traffic signals, lane assignments, and vehicle trajectories becomes feasible, offering notable …

Trajectory data from connected vehicles (CVs) provide a continuous and reliable means of
obtaining information that can be leveraged to optimize traffic signals. This paper proposes a …

With the development of connected and automated vehicles (CAVs) enables real-time
interaction between intersection signals and vehicle trajectories. The full use of this …

Various signal control methods assumed that the bottleneck capacity and traffic volume are
known. However, both may be unknown in nonrecurrent congestion cases, such as traffic …