A Reinforcement Learning-Based Controller Designed for Intersection Signal Suffering from Information Attack
L Ye, K Gao, S Huang, H Huang, R Du - International Conference on …, 2023 - Springer
With the rapid development of smart technology and wireless communication technology,
Intelligent Transportation System (ITS) is considered as an effective way to solve the traffic …
Intelligent Transportation System (ITS) is considered as an effective way to solve the traffic …
Transfer learning method in reinforcement learning-based traffic signal control
Traffic signal control is becoming more important in intelligent transport systems. Existing
studies managed to increase the traffic efficiency on the assumption of a stable traffic …
studies managed to increase the traffic efficiency on the assumption of a stable traffic …
Intelligent traffic signal control based on reinforcement learning with state reduction for smart cities
Efficient signal control at isolated intersections is vital for relieving congestion, accidents,
and environmental pollution caused by increasing numbers of vehicles. However, most of …
and environmental pollution caused by increasing numbers of vehicles. However, most of …
Traffic signal timing via parallel reinforcement learning
Q Zhao, C Xu, S jin - Smart Transportation Systems 2019, 2019 - Springer
Nowadays, reinforcement learning is widely used to design intelligent control algorithms,
which has gradually become one of the popular methods of signal control. We propose a …
which has gradually become one of the popular methods of signal control. We propose a …
[HTML][HTML] Deep reinforcement learning for traffic signal control model and adaptation study
J Tan, Q Yuan, W Guo, N Xie, F Liu, J Wei, X Zhang - Sensors, 2022 - mdpi.com
Deep reinforcement learning provides a new approach to solving complex signal
optimization problems at intersections. Earlier studies were limited to traditional traffic …
optimization problems at intersections. Earlier studies were limited to traditional traffic …
KeyLight: Intelligent Traffic Signal Control Method Based on Improved Graph Neural Network
Y Sun, K Lin, AK Bashir - IEEE Transactions on Consumer …, 2023 - ieeexplore.ieee.org
Graph neural network combined with reinforcement learning is one of the most effective
traffic signal control methods. However, existing methods fail to pay enough attention to the …
traffic signal control methods. However, existing methods fail to pay enough attention to the …
Training reinforcement learning agent for traffic signal control under different traffic conditions
J Zeng, J Hu, Y Zhang - 2019 IEEE Intelligent Transportation …, 2019 - ieeexplore.ieee.org
The model-free reinforcement learning algorithm relieves traffic signal control problem from
complex traffic modeling, and is able to learn a reasonable traffic light control policy from …
complex traffic modeling, and is able to learn a reasonable traffic light control policy from …
An adaptive traffic signal management system incorporating reinforcement learning
Although there has been a lot of study done on traffic monitoring, control, modeling, and the
use of artificial intelligence to handle these problems, there are still a lot of critical problems …
use of artificial intelligence to handle these problems, there are still a lot of critical problems …
[HTML][HTML] Model-based deep reinforcement learning with traffic inference for traffic signal control
H Wang, J Zhu, B Gu - Applied Sciences, 2023 - mdpi.com
In the modern world, the extremely rapid growth of traffic demand has become a major
problem for urban traffic development. Continuous optimization of signal control systems is …
problem for urban traffic development. Continuous optimization of signal control systems is …
Safelight: A reinforcement learning method toward collision-free traffic signal control
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 …
in the US happen at intersections due to problematic signal timing, urging the development …