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Distributed Q-learning controller for a multi-intersection traffic network

Araghi, Sahar, Khosravi, Abbas and Creighton, Douglas 2015, Distributed Q-learning controller for a multi-intersection traffic network, in ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedings, Springer, New York, N.Y., pp. 337-344, doi: 10.1007/978-3-319-26532-2_37.

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Title Distributed Q-learning controller for a multi-intersection traffic network
Author(s) Araghi, Sahar
Khosravi, AbbasORCID iD for Khosravi, Abbas orcid.org/0000-0001-6927-0744
Creighton, Douglas
Conference name Neural Information Processing. Conference (22nd : 2015 : Istanbul, Turkey)
Conference location Istanbul, Turkey
Conference dates 9-12 Nov. 2015
Title of proceedings ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedings
Publication date 2015
Series Lecture Notes in Computer Science v.9489
Start page 337
End page 344
Total pages 8
Publisher Springer
Place of publication New York, N.Y.
Keyword(s) Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
Computer Science
SIGNAL CONTROL
SIMULATION
MANAGEMENT
MODEL
TIME
Summary This paper proposes a Q-learning based controller for a network of multi intersections. According to the increasing amount of traffic congestion in modern cities, using an efficient control system is demanding. The proposed controller designed to adjust the green time for traffic signals by the aim of reducing the vehicles’ travel delay time in a multi-intersection network. The designed system is a distributed traffic timing control model, applies individual controller for each intersection. Each controller adjusts its own intersection’s congestion while attempt to reduce the travel delay time in whole traffic network. The results of experiments indicate the satisfied efficiency of the developed distributed Q-learning controller.
ISBN 9783319265315
ISSN 0302-9743
1611-3349
Language eng
DOI 10.1007/978-3-319-26532-2_37
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
08 Information And Computing Sciences
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30082483

Document type: Conference Paper
Collection: Centre for Intelligent Systems Research
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