Control of a complex traffic junction using fuzzy inference

Fuzzy controllers have been widely used in many consumer products and industrial applications with success over the past two decades. For traffic control, however, fuzzy controllers have not been widely applied. This paper proposes a fuzzy traffic lights controller to be used at a complex traffic ju...

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Main Authors: Yusof, Rubiyah, Khalid, Marzuki, Liang, See Chin
Format: Book Section
Published: IEEE 2004
Subjects:
Online Access:http://eprints.utm.my/7331/
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author Yusof, Rubiyah
Khalid, Marzuki
Liang, See Chin
author_facet Yusof, Rubiyah
Khalid, Marzuki
Liang, See Chin
author_sort Yusof, Rubiyah
building UTeM Institutional Repository
collection Online Access
description Fuzzy controllers have been widely used in many consumer products and industrial applications with success over the past two decades. For traffic control, however, fuzzy controllers have not been widely applied. This paper proposes a fuzzy traffic lights controller to be used at a complex traffic junction in the middle of Kuala Lumpur city, Malaysia. The proposed fuzzy traffic lights controller is capable of communicating with neighbor junctions and manages phase sequences and phase lengths adaptively. A real case study of a complex traffic junction is simulated having 4 intersections. Average flow density, average delay time and link overflow of all the 4 intersections are used as performance indices when comparing the fuzzy controller with two other existing traffic lights controllers in Malaysia, namely the preset-cycle time and vehicle-actuated controllers. A simulator has been developed to show the effectiveness of the fuzzy traffic controller which can also be used for teaching purposes.
first_indexed 2025-11-15T20:58:07Z
format Book Section
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institution Universiti Teknologi Malaysia
institution_category Local University
last_indexed 2025-11-15T20:58:07Z
publishDate 2004
publisher IEEE
recordtype eprints
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spelling utm-73312017-07-25T06:22:57Z http://eprints.utm.my/7331/ Control of a complex traffic junction using fuzzy inference Yusof, Rubiyah Khalid, Marzuki Liang, See Chin QA75 Electronic computers. Computer science Fuzzy controllers have been widely used in many consumer products and industrial applications with success over the past two decades. For traffic control, however, fuzzy controllers have not been widely applied. This paper proposes a fuzzy traffic lights controller to be used at a complex traffic junction in the middle of Kuala Lumpur city, Malaysia. The proposed fuzzy traffic lights controller is capable of communicating with neighbor junctions and manages phase sequences and phase lengths adaptively. A real case study of a complex traffic junction is simulated having 4 intersections. Average flow density, average delay time and link overflow of all the 4 intersections are used as performance indices when comparing the fuzzy controller with two other existing traffic lights controllers in Malaysia, namely the preset-cycle time and vehicle-actuated controllers. A simulator has been developed to show the effectiveness of the fuzzy traffic controller which can also be used for teaching purposes. IEEE 2004 Book Section PeerReviewed Yusof, Rubiyah and Khalid, Marzuki and Liang, See Chin (2004) Control of a complex traffic junction using fuzzy inference. In: 2004 5th Asian Control Conference. IEEE, USA, pp. 1544-1551. ISBN 0780388739 http://ieeexplore.ieee.org/document/1426872/ 10.1109/ASCC.2004.184871
spellingShingle QA75 Electronic computers. Computer science
Yusof, Rubiyah
Khalid, Marzuki
Liang, See Chin
Control of a complex traffic junction using fuzzy inference
title Control of a complex traffic junction using fuzzy inference
title_full Control of a complex traffic junction using fuzzy inference
title_fullStr Control of a complex traffic junction using fuzzy inference
title_full_unstemmed Control of a complex traffic junction using fuzzy inference
title_short Control of a complex traffic junction using fuzzy inference
title_sort control of a complex traffic junction using fuzzy inference
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/7331/
http://eprints.utm.my/7331/
http://eprints.utm.my/7331/