Traffic signal control is safety-critical for our daily life. Roughly one-quarter of road accidents
in the US happen at intersections due to problematic signal timing, urging the development …

Existing inefficient traffic signal plans are causing traffic congestions in many urban areas. In
recent years, many deep reinforcement learning (RL) methods have been proposed to …

Using reinforcement learning for traffic signal control has attracted increasing interests
recently. Various value-based reinforcement learning methods have been proposed to deal …

Deep reinforcement learning (RL) has been applied to traffic signal control recently and
demonstrated superior performance to conventional control methods. However, there are …

Reinforcement learning has been revolutionizing the traditional traffic signal control task,
showing promising power to relieve congestion and improve efficiency. However, the …

Traffic signal control is of critical importance for the effective use of transportation
infrastructures. The rapid increase of vehicle traffic and changes in traffic patterns make …

Traffic signal control is an important and challenging real-world problem that has recently
received a large amount of interest from both transportation and computer science …

Traffic signal control is an important and challenging real-world problem, which aims to
minimize the travel time of vehicles by coordinating their movements at the road …

With the increasing availability of traffic data and advance of deep reinforcement learning
techniques, there is an emerging trend of employing reinforcement learning (RL) for traffic …

A traffic signal is a fundamental part of the traffic control system to reduce congestion and
enhance safety. Since the inception of motorized vehicles, traffic signal controllers are put in …