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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 Creighton
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.

History

Event

Neural Information Processing. Conference (22nd : 2015 : Istanbul, Turkey)

Volume

9489

Series

Lecture Notes in Computer Science v.9489

Pagination

337 - 344

Publisher

Springer

Location

Istanbul, Turkey

Place of publication

New York, N.Y.

Start date

2015-11-09

End date

2015-11-12

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319265315

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2015, IEEE

Title of proceedings

ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedings

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