A dynamic self-improving ramp metering algorithm based on multi-agent deep reinforcement learning

We present a novel ramp metering algorithm that incorporates multi-agent deep reinforcement learning (DRL) techniques, which utilizes monitoring data from loop detectors. Our proposed approach employed a multi-agent DRL framework to generate optimized ramp metering schedules for each ramp meter in r...

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Bibliographic Details

Published in:	Transportation letters Vol. ahead-of-print; no. ahead-of-print; pp. 1 - 9
Main Authors:	Deng, Fuwen, Jin, Jiandong, Shen, Yu, Du, Yuchuan
Format:	Journal Article
Language:	English
Published:	Taylor & Francis 08.08.2024
Subjects:	adaptive control deep reinforcement learning ramp metering
ISSN:	1942-7867, 1942-7875
Online Access:	Get full text
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