Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …
intelligence tool is widely researched to intelligentize communication and networking …
[HTML][HTML] Reinforcement learning in urban network traffic signal control: A systematic literature review
M Noaeen, A Naik, L Goodman, J Crebo, T Abrar… - Expert Systems with …, 2022 - Elsevier
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 …
Future intelligent and secure vehicular network toward 6G: Machine-learning approaches
As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …
and transportation around the world for many years to come. However, with the rapid growth …
A deep reinforcement learning network for traffic light cycle control
Existing inefficient traffic light cycle control causes numerous problems, such as long delay
and waste of energy. To improve efficiency, taking real-time traffic information as an input …
and waste of energy. To improve efficiency, taking real-time traffic information as an input …
Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks
As urban traffic condition is diverse and complicated, applying reinforcement learning to
reduce traffic congestion becomes one of the hot and promising topics. Especially, how to …
reduce traffic congestion becomes one of the hot and promising topics. Especially, how to …
Intelligent resource management based on reinforcement learning for ultra-reliable and low-latency IoV communication networks
Internet of Vehicles (IoV) has attracted much interest recently due to its ubiquitous message
exchange and content sharing among smart vehicles with the development of the mobile …
exchange and content sharing among smart vehicles with the development of the mobile …
Traffic signal control for smart cities using reinforcement learning
H Joo, SH Ahmed, Y Lim - Computer Communications, 2020 - Elsevier
Traffic congestion is increasing globally, and this problem needs to be addressed by the
traffic management system. Traffic signal control (TSC) is an effective method among various …
traffic management system. Traffic signal control (TSC) is an effective method among various …
Unsupervised deep learning for IoT time series
Internet of Things (IoT) time-series analysis has found numerous applications in a wide
variety of areas, ranging from health informatics to network security. Nevertheless, the …
variety of areas, ranging from health informatics to network security. Nevertheless, the …
[HTML][HTML] Fuzzy logic and deep Q learning based control for traffic lights
I Tunc, MT Soylemez - Alexandria Engineering Journal, 2023 - Elsevier
Traffic congestion is a major concern for many metropolises. Although it is difficult to regulate
traffic flow because of numerous complexities and uncertainties, the traffic congestion …
traffic flow because of numerous complexities and uncertainties, the traffic congestion …
A review of reinforcement learning applications in adaptive traffic signal control
In urban areas, the problem of recurring daily congestion is constantly increasing. A possible
solution is seen in the application of adaptive traffic signal control (ATSC) systems for the …
solution is seen in the application of adaptive traffic signal control (ATSC) systems for the …