Management of Vehicular Traffic System using Artificial Bee Colony Algorithm

In this paper, an Adaptive Dynamic Scheduling Algorithm (ADSA) based on Artificial Bee Colony (ABC) was developed for vehicular traffic control. The developed model optimally scheduled green light timing in accordance with traffic condition in order to minimize the Average Waiting Time (AWT) at the...

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Vydáno v:International journal of image, graphics and signal processing Ročník 9; číslo 11; s. 18 - 28
Hlavní autoři: O. Adebiyi, Risikat Folashade, Ahmad Abubilal, Kabir, Sunkary Tekanyi, Abdoulie Momodou, Hadir Adebiyi, Busayo
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hong Kong Modern Education and Computer Science Press 08.11.2017
Témata:
Adaptive algorithms
Adaptive systems
Computer simulation
Graphical user interface
Queues
Queuing theory
Search algorithms
Swarm intelligence
Traffic control
Traffic management
Traffic models
ISSN:2074-9074, 2074-9082
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Abstract In this paper, an Adaptive Dynamic Scheduling Algorithm (ADSA) based on Artificial Bee Colony (ABC) was developed for vehicular traffic control. The developed model optimally scheduled green light timing in accordance with traffic condition in order to minimize the Average Waiting Time (AWT) at the cross intersection. A MATLAB based Graphic User Interface (GUI) traffic control simulator was developed. In order to demonstrate the effectiveness of the developed ADSA this paper was validated with the existing work in the literature. The result obtained for the AWT of the developed ADSA had a performance of 76.67%. While for vehicular queues cleared at the intersection the developed ADSA had a performance of 53.33%. The results clearly expressed that the developed ADSA method has been successful in minimizing the Average Waiting Time and vehicular queues at the intersection.
AbstractList In this paper, an Adaptive Dynamic Scheduling Algorithm (ADSA) based on Artificial Bee Colony (ABC) was developed for vehicular traffic control. The developed model optimally scheduled green light timing in accordance with traffic condition in order to minimize the Average Waiting Time (AWT) at the cross intersection. A MATLAB based Graphic User Interface (GUI) traffic control simulator was developed. In order to demonstrate the effectiveness of the developed ADSA this paper was validated with the existing work in the literature. The result obtained for the AWT of the developed ADSA had a performance of 76.67%. While for vehicular queues cleared at the intersection the developed ADSA had a performance of 53.33%. The results clearly expressed that the developed ADSA method has been successful in minimizing the Average Waiting Time and vehicular queues at the intersection.
Author O. Adebiyi, Risikat Folashade
Hadir Adebiyi, Busayo
Ahmad Abubilal, Kabir
Sunkary Tekanyi, Abdoulie Momodou
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CorporateAuthor Ahmadu Bello University/Department of Electrical and Computer Engineering, Zaria, 234, Nigeria
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SubjectTerms Adaptive algorithms
Adaptive systems
Computer simulation
Graphical user interface
Queues
Queuing theory
Search algorithms
Swarm intelligence
Traffic control
Traffic management
Traffic models
Title Management of Vehicular Traffic System using Artificial Bee Colony Algorithm
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