A FRAMEWORK FOR FOG VIRTUAL TRAFFIC LIGHT SYSTEM | [Journal of Theoretical and Applied Information Technology • 2020]

Author(s):

1. MUSTAFA BANIKHALAF: Yarmouk University, Faculty of Information Technology and Computer Science, Irbid, Jordan

2. MOHAMMAD ASHRAF OTTOM: Yarmouk University, Faculty of Information Technology and Computer Science, Irbid, Jordan

3. MAMOON OBIEDAT: Hashimiate University, Department of Applied Computer Science, Al-araba, Jordan

4. NABHAN HAMADNEH: Hashimiate University, Department of Applied Computer Science, Al-araba, Jordan

Abstract:

Traffic congestions at intersections inside urban cities gain a considerable research interest. Traditional physical traffic light systems become unable to manage traffic congestions efficiently due to a vast increase on the number of vehicles on the roads. Recently, Virtual Traffic light (VTL) system technology based vehicular communications has attracted research community and industry. The emerging field of Fog computing and vehicular networks make replacing traditional physical traffic light systems by VTL system is cost-effective. Hence, the main contribution of this paper is divided into two parts. First part is to provide a taxonomy of the research on traffic light systems and traffic congestions based different vehicular communications. The second part is to design a new framework to implement VTL system based on fog computing architecture namely F-VTL. In contrast to traditional VTL system, the algorithm that operates the F-VTL dynamically manages vehicles passing unsignalized intersections. In F-VTL system, a fog node is responsible to collect and processes data from vehicles on a regular base to control F-VTL system. Simulation experiments show that F-VTL has better performance compared to the traditional VTL system.

Page(s): 279-289

DOI: DOI not available

Published: Journal: Journal of Theoretical and Applied Information Technology, Volume: 98, Issue: 2, Year: 2020

Keywords:

Vehicular communication , Virtual Traffic Light , Traffic Congestions

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