A physics-informed reinforcement learning-based strategy for local and coordinated ramp metering-Reference-Cited by-同舟云学术

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A physics-informed reinforcement learning-based strategy for local and coordinated ramp metering

Published:2022-04 Issue: Volume:137 Page:103584
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Han Yu,Wang Meng^ORCID,Li Linghui^ORCID,Roncoli Claudio,Gao Jinda,Liu Pan

Funder

Academy of Finland

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference52 articles.

1. Expert level control of ramp metering based on multi-task deep reinforcement learning;Belletti;IEEE Trans. Intell. Transp. Syst.,2017

2. Isolated versus coordinated ramp metering: Field evaluation results of travel time reliability and traffic impact;Bhouri;Transp. Res. C,2013

3. Multi-agent deep reinforcement learning for large-scale traffic signal control;Chu;IEEE Trans. Intell. Transp. Syst.,2019

4. Motorway ramp-metering control with queuing consideration using q-learning;Davarynejad,2011

5. Multiagent reinforcement learning for integrated network of adaptive traffic signal controllers (marlin-atsc): methodology and large-scale application on downtown toronto;El-Tantawy;IEEE Trans. Intell. Transp. Syst.,2013

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