Nonlinear Decision Rule Approach for Real-Time Traffic Signal Control for Congestion and Emission Mitigation-Reference-Cited by-同舟云学术

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Nonlinear Decision Rule Approach for Real-Time Traffic Signal Control for Congestion and Emission Mitigation

Published:2020-06-01 Issue:3 Volume:20 Page:675-702
ISSN:1566-113X
Container-title:Networks and Spatial Economics
language:en
Short-container-title:Netw Spat Econ

Author:

Song Junwoo,Hu Simon,Han Ke,Jiang Chaozhe

Funder

EU 7th Framework Program

National Social Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,Software

Link

https://link.springer.com/content/pdf/10.1007/s11067-020-09497-3.pdf

Reference57 articles.

1. Arel L, Liu C, Urbanik T, Kohls AG (2010) Reinforcement learning-based multi-agent system for network traffic signal control. IET Intell Transp Syst 4 (2):128–135

2. Balaji PG, German X, Srinivasan D (2010) Urban traffic signal control using reinforcement learning agents. IET Intell Transp Syst 4(3):177–188

3. Banks A, Vincent J, Anyakoha C (2007) A review of particle swarm optimization. Part I: background and development. Nat Comput 6(4):467–484

4. Bertsimas D, Brown DB, Caramanis C (2011) Theory and applications of robust optimization. SIAM Rev 53(3):464–501

5. Cai C, Wong CK, Heydecker BG (2009) Adaptive traffic signal control using approximate dynamic programming. Transp Res Part C: Emerg Technol 17 (5):456–474

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