Multi-agent reinforcement learning for traffic signal control through universal communication method

Multi-agent reinforcement learning for traffic signal control through universal communication method

How to coordinate the communication among intersections effectively in real complex traffic scenarios with multi-intersection is challenging. Existing approaches only enable the communication in a heuristic manner without considering the content/importance of information to be shared. In this paper,...

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Bibliographic Details
Main Authors: JIANG, Qize, QIN, Minhao, SHI, Shengmin, SUN, Weiwei Sun, ZHENG, Baihua
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2022
Subjects:
Transportation
traffic control
UniComm
Databases and Information Systems
Operations Research, Systems Engineering and Industrial Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/7193
https://ink.library.smu.edu.sg/context/sis_research/article/8196/viewcontent/Multi_Agent_Reinforcement_Learning_for_Traffic_Signal_Control_through_UniversalCommunication_Method__3_.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/sis_research/7193
https://ink.library.smu.edu.sg/context/sis_research/article/8196/viewcontent/Multi_Agent_Reinforcement_Learning_for_Traffic_Signal_Control_through_UniversalCommunication_Method__3_.pdf

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