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Distributed Q-learning controller for a multi-intersection traffic network
conference contribution
posted on 2015-01-01, 00:00 authored by Sahar Araghi, Abbas KhosraviAbbas Khosravi, Douglas CreightonDouglas CreightonThis 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.
History
Event
Neural Information Processing. Conference (22nd : 2015 : Istanbul, Turkey)Volume
9489Series
Lecture Notes in Computer Science v.9489Pagination
337 - 344Publisher
SpringerLocation
Istanbul, TurkeyPlace of publication
New York, N.Y.Publisher DOI
Start date
2015-11-09End date
2015-11-12ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319265315Publication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2015, IEEETitle of proceedings
ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedingsUsage metrics
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