[HTML][HTML] Reinforcement learning in urban network traffic signal control: A systematic literature review
Improvement of traffic signal control (TSC) efficiency has been found to lead to improved
urban transportation and enhanced quality of life. Recently, the use of reinforcement …
urban transportation and enhanced quality of life. Recently, the use of reinforcement …
[HTML][HTML] Leveraging reinforcement learning for dynamic traffic control: A survey and challenges for field implementation
In recent years, the advancement of artificial intelligence techniques has led to significant
interest in reinforcement learning (RL) within the traffic and transportation community …
interest in reinforcement learning (RL) within the traffic and transportation community …
Toward a thousand lights: Decentralized deep reinforcement learning for large-scale traffic signal control
Traffic congestion plagues cities around the world. Recent years have witnessed an
unprecedented trend in applying reinforcement learning for traffic signal control. However …
unprecedented trend in applying reinforcement learning for traffic signal control. However …
Presslight: Learning max pressure control to coordinate traffic signals in arterial network
Traffic signal control is essential for transportation efficiency in road networks. It has been a
challenging problem because of the complexity in traffic dynamics. Conventional …
challenging problem because of the complexity in traffic dynamics. Conventional …
A survey on traffic signal control methods
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 …
minimize the travel time of vehicles by coordinating their movements at the road …
Learning phase competition for traffic signal control
Increasingly available city data and advanced learning techniques have empowered people
to improve the efficiency of our city functions. Among them, improving urban transportation …
to improve the efficiency of our city functions. Among them, improving urban transportation …
Metalight: Value-based meta-reinforcement learning for traffic signal control
Using reinforcement learning for traffic signal control has attracted increasing interests
recently. Various value-based reinforcement learning methods have been proposed to deal …
recently. Various value-based reinforcement learning methods have been proposed to deal …
[HTML][HTML] Deep reinforcement learning for traffic signal control with consistent state and reward design approach
Abstract Intelligent Transportation Systems are essential due to the increased number of
traffic congestion problems and challenges nowadays. Traffic Signal Control (TSC) plays a …
traffic congestion problems and challenges nowadays. Traffic Signal Control (TSC) plays a …
[HTML][HTML] Future wireless communication technology towards 6G IoT: An application-based analysis of IoT in real-time location monitoring of employees inside …
In recent years, the IoT has emerged as the most promising technology in the key evolution
of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and …
of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and …
[HTML][HTML] Application of deep reinforcement learning in traffic signal control: An overview and impact of open traffic data
Persistent congestions which are varying in strength and duration in the dense traffic
networks are the most prominent obstacle towards sustainable mobility. Those types of …
networks are the most prominent obstacle towards sustainable mobility. Those types of …