A deep reinforcement learning-based cooperative approach for multi-intersection traffic signal control
Abstract Recently, Adaptive Traffic Signal Control (ATSC) in the multi-intersection system is
considered as one of the most critical issues in Intelligent Transportation Systems (ITS) …
considered as one of the most critical issues in Intelligent Transportation Systems (ITS) …
[HTML][HTML] CCGN: Centralized collaborative graphical transformer multi-agent reinforcement learning for multi-intersection signal free-corridor
Tackling traffic signal control through multi-agent reinforcement learning is a widely-
employed approach. However, current state-of-the-art models have drawbacks: intersections …
employed approach. However, current state-of-the-art models have drawbacks: intersections …
Multi-agent reinforcement learning for traffic signal control: A cooperative approach
The rapid growth of urbanization and the constant demand for mobility have put a great
strain on transportation systems in cities. One of the major challenges in these areas is traffic …
strain on transportation systems in cities. One of the major challenges in these areas is traffic …
Multi-objective traffic signal control using network-wide agent coordinated reinforcement learning
J Fang, Y You, M Xu, J Wang, S Cai - Expert Systems with Applications, 2023 - Elsevier
The optimization of intersection signal control can improve traffic efficiency, reduce
congestion degree, and improve traffic safety. Aiming at implementing the coordinated …
congestion degree, and improve traffic safety. Aiming at implementing the coordinated …
Traffic Congestion Detection from Surveillance Videos using Deep Learning
GB Madhavi, AD Bhavani, YS Reddy… - … Engineering & their …, 2023 - ieeexplore.ieee.org
Countless cameras, both public and private, have been installed in recent years for the
objectives of surveillance, the monitoring of anomalous human activities, and traffic …
objectives of surveillance, the monitoring of anomalous human activities, and traffic …
[HTML][HTML] Internet of Things and Distributed Computing Systems in Business Models
AT Rosário, R Raimundo - Future Internet, 2024 - mdpi.com
The integration of the Internet of Things (IoT) and Distributed Computing Systems (DCS) is
transforming business models across industries. IoT devices allow immediate monitoring of …
transforming business models across industries. IoT devices allow immediate monitoring of …
Transformerlight: A novel sequence modeling based traffic signaling mechanism via gated transformer
Traffic signal control (TSC) is still one of the most significant and challenging research
problems in the transportation field. Reinforcement learning (RL) has achieved great …
problems in the transportation field. Reinforcement learning (RL) has achieved great …
Multiple intersections traffic signal control based on cooperative multi-agent reinforcement learning
For the multi-agent traffic signal controls, the traffic signal at each intersection is controlled
by an independent agent. Since the control policy for each agent is dynamic, when the traffic …
by an independent agent. Since the control policy for each agent is dynamic, when the traffic …
Traffic signal control using reinforcement learning based on the teacher-student framework
Reinforcement Learning (RL) is an effective method for adaptive traffic signals control. As
one type of RL, the teacher-student framework has been found helpful in improving the …
one type of RL, the teacher-student framework has been found helpful in improving the …
Towards explainable traffic signal control for urban networks through genetic programming
The increasing number of vehicles in urban areas draws significant attention to traffic signal
control (TSC), which can enhance the efficiency of the entire network by properly switching …
control (TSC), which can enhance the efficiency of the entire network by properly switching …