Deep reinforcement learning for traffic signal control: A review
… traffic congestion. This article presents a review of the attributes of traffic signal control (TSC)…
has been applied to address traffic congestion and achieve performance enhancement. The …
has been applied to address traffic congestion and achieve performance enhancement. The …
[HTML][HTML] Reinforcement learning in urban network traffic signal control: A systematic literature review
… , and speed) by controlling the actions of the agents. The main focus of this paper is …
controlling the timing of traffic signal agents, although this control can be integrated with the control …
controlling the timing of traffic signal agents, although this control can be integrated with the control …
A review of reinforcement learning applications in adaptive traffic signal control
… the controller to learn the optimal control policy by direct interaction with the environment. This
paper describes the fundamentals of traffic signal control, … on future traffic signal control. In …
paper describes the fundamentals of traffic signal control, … on future traffic signal control. In …
Application of deep reinforcement learning in traffic signal control: An overview and impact of open traffic data
… An overview of DRL frameworks for traffic signal control provided in this paper represents …
for traffic signal control. Those frameworks are analyzed with respect to their learning hyper-…
for traffic signal control. Those frameworks are analyzed with respect to their learning hyper-…
Recent advances in reinforcement learning for traffic signal control: A survey of models and evaluation
… techniques they use and provide a review of existing models with analysis … traffic signal
control methods. Finally, we explore future directions in the area of RLbased traffic signal control …
control methods. Finally, we explore future directions in the area of RLbased traffic signal control …
Deep learning vs. discrete reinforcement learning for adaptive traffic signal control
SMA Shabestary, B Abdulhai - 2018 21st International …, 2018 - ieeexplore.ieee.org
… LITERATURE REVIEW Traffic controllers are classified into three main categories: Fixed-…
of deep learning to handle high-dimensional state space, we design the traffic signal controller …
of deep learning to handle high-dimensional state space, we design the traffic signal controller …
Deep reinforcement learning based approach for traffic signal control
… study using a high-fidelity microscopic traffic simulator. The results justify that the Deep
Reinforcement Learning based approach is a real candidate for real-time traffic light control. …
Reinforcement Learning based approach is a real candidate for real-time traffic light control. …
Robust deep reinforcement learning for traffic signal control
… agents that can handle such noisy approximation of the traffic … during training, the reinforcement
learning agents can be … reinforcement learning agent-based traffic signal controllers. …
learning agents can be … reinforcement learning agent-based traffic signal controllers. …
Using a deep reinforcement learning agent for traffic signal control
… For a comprehensive review of reinforcement learning traffic signal control research, the
reader is referred to [16] and [17]. Regarding previous research, the following observations can …
reader is referred to [16] and [17]. Regarding previous research, the following observations can …
A critical review of traffic signal control and a novel unified view of reinforcement learning and model predictive control approaches for adaptive traffic signal control
… For this purpose, this article proposes the unified view describing generic traffic signal
control (TSC) problems in the form of mixed observability Markov decision processes (MOMDP), …
control (TSC) problems in the form of mixed observability Markov decision processes (MOMDP), …