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,...
Saved in:
Main Authors: | JIANG, Qize, QIN, Minhao, SHI, Shengmin, SUN, Weiwei Sun, ZHENG, Baihua |
---|---|
格式: | text |
語言: | English |
出版: |
Institutional Knowledge at Singapore Management University
2022
|
主題: | |
在線閱讀: | 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 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Singapore Management University |
語言: | English |
相似書籍
-
Dynamic lane traffic signal control with group attention and multi-timescale reinforcement learning
由: JIANG, Qize, et al.
出版: (2021) -
Attention based graph Bi-LSTM networks for traffic forecasting
由: Zhao, Han, et al.
出版: (2021) -
Outsmarting traffic? A traffic complexity simulation of the effect of traffic information apps on traffic congestion
由: Azcarraga, Arno Mikhail J., et al.
出版: (2020) -
Microscopic road traffic scene analysis using computer vision and traffic flow modelling
由: Billones, Robert Kerwin C., et al.
出版: (2018) -
A spatial-temporal network perspective for the propagation dynamics of air traffic delays
由: Cai, Qing, et al.
出版: (2021)