Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems Part 2—Applications …
The two-part series of papers provides a survey on recent advances in Deep Reinforcement
Learning (DRL) for solving partially observable Markov decision processes (POMDP) …
Learning (DRL) for solving partially observable Markov decision processes (POMDP) …
Robust deep reinforcement learning for traffic signal control
A traffic signal is a fundamental part of the traffic control system to reduce congestion and
enhance safety. Since the inception of motorized vehicles, traffic signal controllers are put in …
enhance safety. Since the inception of motorized vehicles, traffic signal controllers are put in …
Adaptive traffic signal control using distributed marl and federated learning
T Wang, T Liang, J Li, W Zhang… - 2020 IEEE 20th …, 2020 - ieeexplore.ieee.org
Facing the increasingly serious traffic congestion problem, the existing traffic signal control
technology has been unable to meet the demands of urban smart traffic construction. As one …
technology has been unable to meet the demands of urban smart traffic construction. As one …
Boosting the Training of Deep Reinforcement Learning Traffic Control by Using the World Model
Deep reinforcement learning (DRL) traffic control attracts increasing interest since it is widely
viewed as a powerful tool for alleviating congestion that significantly impacts people's daily …
viewed as a powerful tool for alleviating congestion that significantly impacts people's daily …
WaveLearner: A Knowledge-Combined Reinforcement Learning to Understand Coordinated Traffic Signal Control along Urban Arteries
With the development of detection and computation techniques, the use of reinforcement
learning (RL) in traffic signal control problems is widely discussed. After formulating diverse …
learning (RL) in traffic signal control problems is widely discussed. After formulating diverse …
Reinforcement Learning Approach to Adaptive Traffic Signal Control Using SUMO-RL
Traffic control in urban environments is a complex and critical challenge, with growing
urbanisation and increasing vehicular congestion necessitating innovative solutions …
urbanisation and increasing vehicular congestion necessitating innovative solutions …
Data-driven Optimal Traffic Signal Control with Phase Priority and Switching Cost
X Li, J Jiang - 2024 12th International Conference on Intelligent …, 2024 - ieeexplore.ieee.org
In this paper, a model-free scheme is proposed to solve the optimal traffic signal control of
multi-intersection system. First, the model of the traffic network is constructed as a switching …
multi-intersection system. First, the model of the traffic network is constructed as a switching …
[PDF][PDF] An adaptive traffic light control system using reinforcement learning.
K Jearanaitanakij, C Jamkhaw… - … Journal of Science & …, 2022 - researchgate.net
Traffic signal control (TSC) is a challenging issue in managing an urban transportation
system. A fixed time TSC is easy to implement but has drawbacks in such measures as flow …
system. A fixed time TSC is easy to implement but has drawbacks in such measures as flow …
Akıllı şehirler için koordineli adaptif trafik sinyalizasyon kontrolü
MEM Ali - 2021 - acikerisim.selcuk.edu.tr
Özet Geçen yüzyılın başından itibaren araç sayısının her geçen gün artması nedeniyle trafik
sinyal kontrol sistemleri ilgi çekmeye başlamıştır. Bu durum, büyük ve kalabalık şehirlerde …
sinyal kontrol sistemleri ilgi çekmeye başlamıştır. Bu durum, büyük ve kalabalık şehirlerde …