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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OMICS International
2017
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Online Access: | http://umpir.ump.edu.my/id/eprint/25455/1/An%20integrated%20model%20to%20control%20traffic%20lights%20.pdf http://umpir.ump.edu.my/id/eprint/25455/ 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 |
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my.ump.umpir.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 |
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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 |
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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. |
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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/25455/1/An%20integrated%20model%20to%20control%20traffic%20lights%20.pdf http://umpir.ump.edu.my/id/eprint/25455/ 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 |
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