Cooperative traffic optimization with multi-agent reinforcement learning and evolutionary strategy: Bridging the gap between micro and macro traffic control-Reference-Cited by-同舟云学术

Cooperative traffic optimization with multi-agent reinforcement learning and evolutionary strategy: Bridging the gap between micro and macro traffic control

Published:2024-08 Issue: Volume:647 Page:129734
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Feng Jianshuai^ORCID,Lin Kaize,Shi Tianyu,Wu Yuankai,Wang Yong,Zhang Hailong,Tan Huachun

Funder

Ministry of Science and Technology of the People's Republic of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Reference45 articles.

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4. Deep multi-agent reinforcement learning for highway on-ramp merging in mixed traffic;Chen;IEEE Trans. Intell. Transp. Syst.,2023

5. Driving decision and control for autonomous lane change based on deep reinforcement learning;Shi,2019

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