Intersections are prone to congestion in urban areas and making competent speed plans for
vehicles to efficiently utilize green time resources is significant for congestion alleviation and …

Traffic congestion alleviation around intersections has been a growing challenge, and a
competent traffic signal control scheme plays a pivotal role in intelligent transportation …

Active Traffic Management strategies are often adopted in real-time to address such sudden
flow breakdowns. When queuing is imminent, Speed Harmonization (SH), which adjusts …

The efficiency of traffic flows in urban areas largely depends on signal operation. The state-
of-the-art traffic signal control strategies are not able to efficiently deal with varying or over …

Traffic congestion in dense urban centers presents an economical and environmental
burden. In recent years, the availability of vehicle-to-anything communication allows for the …

To address traffic congestion in urban expressways during the transition from wide to narrow
sections, this study proposed a car-following strategy based on deep reinforcement learning …

In this paper, we examine the practical problem of minimizing the delay in traffic networks
that are controlled at each intersection independently, without a centralized supervisory …

Reinforcement learning (RL)–based car-following (CF) control strategies have attracted
significant attention in academia, emerging as a prominent research topic in recent years …

In smart cities, with large numbers of vehicles on roads, including autonomous and manned
ones, congestion is still a significant issue and hence smart traffic signal control is …

Adaptive cruise control (ACC) systems are increasingly offered in new vehicles in the market
today, and they form a core building block for future full autonomous driving. ACC systems …