We present a novel ramp metering algorithm that incorporates multi-agent deep
reinforcement learning (DRL) techniques, which utilizes monitoring data from loop detectors …

Ramp metering has been considered as one of the most effective approaches of dealing
with the traffic congestion on the freeways. The modelling of the freeway traffic flow …

In the development of smart cities, the transportation system plays a crucial role, with road
congestion being particularly prominent under conditions of long-distance travel and high …

Lane changing behavior has a significant impact on traffic efficiency and may lead to traffic
delays or even accidents. It is important to plan a safe and efficient lane‐changing trajectory …

This study proposed an on-ramp cooperative control strategy for connected and automated
vehicles (CAVs) based on the virtual platoon method. First, the formation rules of the virtual …

The demand for a secure lifestyle and travel is increasing due to the rapid development of
technology. Since the turn of the century, the number of road vehicles has risen dramatically …

This paper introduces an action replacement module for reinforcement learning (RL)–based
ramp metering to address the issue of ramp queue spillback during the training process …

Autonomous vehicles (AVs) can significantly promote the advances in road transport
mobility in terms of safety, reliability, and decarbonization. However, ensuring safety and …

Control measures at merging locations aimed at either the mainline traffic or on‐ramp traffic
do not lead to a fairness in the distribution of total delay across the two streams. This paper …

In order to solve the problems of slow response and inaccurate control of the traditional
ramp metering algorithm, we propose an intelligent ramp metering model based on deep …