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Genetic algorithm application for traffic light control

In this paper, we describe the design of an intelligent traffic light control based on genetic algorithm. This paper is part of our work in which we attempt to use genetic algorithm in traffic light control and pedestrian crossing. In our approach, we use four sensors; each sensor calculates the veh...

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Main Authors:	Turky A.M., Ahmad M.S., Yusoff M.Z.M., Sabar N.R.
Other Authors:	25825717300
Format:	Conference paper
Published:	Springer Verlag 2023
Subjects:	Controllers Genetic algorithms Information systems Sensors Fixed time Genetic algorithm applications Isolated intersections Pedestrian crossings Traffic light controls Vehicle densities Genetic engineering
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id	my.uniten.dspace-30844
record_format	dspace
spelling	my.uniten.dspace-308442023-12-29T15:54:28Z Genetic algorithm application for traffic light control Turky A.M. Ahmad M.S. Yusoff M.Z.M. Sabar N.R. 25825717300 7402895985 22636590200 25825697600 Controllers Genetic algorithms Information systems Sensors Fixed time Genetic algorithm applications Isolated intersections Pedestrian crossings Traffic light controls Vehicle densities Genetic engineering In this paper, we describe the design of an intelligent traffic light control based on genetic algorithm. This paper is part of our work in which we attempt to use genetic algorithm in traffic light control and pedestrian crossing. In our approach, we use four sensors; each sensor calculates the vehicle density for each lane. We developed an algorithm to simulate the situation of an isolated intersection (four lanes) based on this technology. We then compare the performance between the genetic algorithm controller and a conventional fixed time controller. � 2009 Springer Berlin Heidelberg. Final 2023-12-29T07:54:28Z 2023-12-29T07:54:28Z 2009 Conference paper 10.1007/978-3-642-01112-2_12 2-s2.0-65349145239 https://www.scopus.com/inward/record.uri?eid=2-s2.0-65349145239&doi=10.1007%2f978-3-642-01112-2_12&partnerID=40&md5=760e4ced4ea8e18a276c8ca5fb137e45 https://irepository.uniten.edu.my/handle/123456789/30844 20 LNBIP 115 120 Springer Verlag Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Controllers Genetic algorithms Information systems Sensors Fixed time Genetic algorithm applications Isolated intersections Pedestrian crossings Traffic light controls Vehicle densities Genetic engineering
spellingShingle	Controllers Genetic algorithms Information systems Sensors Fixed time Genetic algorithm applications Isolated intersections Pedestrian crossings Traffic light controls Vehicle densities Genetic engineering Turky A.M. Ahmad M.S. Yusoff M.Z.M. Sabar N.R. Genetic algorithm application for traffic light control
description	In this paper, we describe the design of an intelligent traffic light control based on genetic algorithm. This paper is part of our work in which we attempt to use genetic algorithm in traffic light control and pedestrian crossing. In our approach, we use four sensors; each sensor calculates the vehicle density for each lane. We developed an algorithm to simulate the situation of an isolated intersection (four lanes) based on this technology. We then compare the performance between the genetic algorithm controller and a conventional fixed time controller. � 2009 Springer Berlin Heidelberg.
author2	25825717300
author_facet	25825717300 Turky A.M. Ahmad M.S. Yusoff M.Z.M. Sabar N.R.
format	Conference paper
author	Turky A.M. Ahmad M.S. Yusoff M.Z.M. Sabar N.R.
author_sort	Turky A.M.
title	Genetic algorithm application for traffic light control
title_short	Genetic algorithm application for traffic light control
title_full	Genetic algorithm application for traffic light control
title_fullStr	Genetic algorithm application for traffic light control
title_full_unstemmed	Genetic algorithm application for traffic light control
title_sort	genetic algorithm application for traffic light control
publisher	Springer Verlag
publishDate	2023
_version_	1806425791152521216
score	13.222552

Genetic algorithm application for traffic light control

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