An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm

In this paper we propose an integrated model combines Fuzzy Logic (FL) and Genetic Algorithm (GA), utilizing their applications in order to minimize the traffic congestion and traffic delay, through controlling traffic light system in three proposed traffic intersections. The proposed model in this...

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Main Authors:	Khaled Abdul Rahman, Jomaa, Cheng, Jack Kie
Format:	Article
Language:	English
Published:	OMICS International 2017
Subjects:	QA Mathematics T Technology (General) TK Electrical engineering. Electronics Nuclear engineering TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/25455/ http://umpir.ump.edu.my/id/eprint/25455/ http://umpir.ump.edu.my/id/eprint/25455/ http://umpir.ump.edu.my/id/eprint/25455/1/An%20integrated%20model%20to%20control%20traffic%20lights%20.pdf

id	ump-25455
recordtype	eprints
spelling	ump-254552020-02-11T04:46:19Z http://umpir.ump.edu.my/id/eprint/25455/ An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm Khaled Abdul Rahman, Jomaa Cheng, Jack Kie QA Mathematics T Technology (General) TK Electrical engineering. Electronics Nuclear engineering TS Manufactures In this paper we propose an integrated model combines Fuzzy Logic (FL) and Genetic Algorithm (GA), utilizing their applications in order to minimize the traffic congestion and traffic delay, through controlling traffic light system in three proposed traffic intersections. The proposed model in this paper will adjust the timing and phasing of the green traffic lights according to the current situation in the proposed traffic intersections; each intersection is supposed to be controlled by traffic signals that will apply the model. The green light interval time length shall provide at an intersection will be decided by FL. the outputs of FL will be optimized by GA, in order to obtain a higher performance. This performance can be measured considering the reduction in the waiting time and the total amount of vehicles that arrived to the Queue of the three intersections. The proposed model expected to provide a significant improvement to the traffic light system performance which might be very important to be applied in the metropolitan areas in Malaysia. OMICS International 2017-02 Article PeerReviewed pdf en cc_by_nd_4 http://umpir.ump.edu.my/id/eprint/25455/1/An%20integrated%20model%20to%20control%20traffic%20lights%20.pdf Khaled Abdul Rahman, Jomaa and Cheng, Jack Kie (2017) An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm. Business and Economics Journal, 8 (1). pp. 1-9. ISSN 2151-6219 https://www.omicsonline.org/open-access/an-integrated-model-to-control-traffic-lights-controlling-of-traffic-lightsin-multiple-intersections-using-fuzzy-logic-and-genetic-2151-6219-1000287.pdf https://doi.org/10.4172/2151-6219.1000287
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA Mathematics T Technology (General) TK Electrical engineering. Electronics Nuclear engineering TS Manufactures
spellingShingle	QA Mathematics T Technology (General) TK Electrical engineering. Electronics Nuclear engineering TS Manufactures Khaled Abdul Rahman, Jomaa Cheng, Jack Kie An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm
description	In this paper we propose an integrated model combines Fuzzy Logic (FL) and Genetic Algorithm (GA), utilizing their applications in order to minimize the traffic congestion and traffic delay, through controlling traffic light system in three proposed traffic intersections. The proposed model in this paper will adjust the timing and phasing of the green traffic lights according to the current situation in the proposed traffic intersections; each intersection is supposed to be controlled by traffic signals that will apply the model. The green light interval time length shall provide at an intersection will be decided by FL. the outputs of FL will be optimized by GA, in order to obtain a higher performance. This performance can be measured considering the reduction in the waiting time and the total amount of vehicles that arrived to the Queue of the three intersections. The proposed model expected to provide a significant improvement to the traffic light system performance which might be very important to be applied in the metropolitan areas in Malaysia.
format	Article
author	Khaled Abdul Rahman, Jomaa Cheng, Jack Kie
author_facet	Khaled Abdul Rahman, Jomaa Cheng, Jack Kie
author_sort	Khaled Abdul Rahman, Jomaa
title	An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm
title_short	An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm
title_full	An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm
title_fullStr	An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm
title_full_unstemmed	An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm
title_sort	integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm
publisher	OMICS International
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/25455/ http://umpir.ump.edu.my/id/eprint/25455/ http://umpir.ump.edu.my/id/eprint/25455/ http://umpir.ump.edu.my/id/eprint/25455/1/An%20integrated%20model%20to%20control%20traffic%20lights%20.pdf
first_indexed	2023-09-18T22:39:06Z
last_indexed	2023-09-18T22:39:06Z
_version_	1777416794541129728

An integrated model to control traffic lights : controlling of traffic lights in multiple intersections using fuzzy logic and genetic algorithm

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