Integrated self-organized traffic light controllers for signalized intersections

Abbas, M.K. and Karsiti, M.N. and Napiah, M. and Brahim, S. (2013) Integrated self-organized traffic light controllers for signalized intersections. International Review of Automatic Control, 6 (4). pp. 481-488. ISSN 19746059

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

Detecting emergency vehicles arrival on roads has been the focus for many researchers. It is quite important to detect the emergency vehicles (e.g; ambulance) arrival to traffic light to give the green light for it to pass through. Many researchers have suggested and patented emergency vehicles detection systems however, according to our knowledge, none of them considered solving the effect of giving extra green time to a road while the queues are being built on others. This paper considers the problem of finding a better traffic light phase plan to stabilize/recover the situation at an effected intersection after solving an emergency vehicle existence. A hardware setup and a novel messaging protocol have been suggested to be set on roads and vehicles to collect roads real time data. In addition, a novel decision making protocol has been created to make the use of the collected data for making a better traffic light phase plan for an intersection. The phase plan has two main decisions to be made; which light has a higher priority to be green in the next phase, and how long the green phase should be. After simulating the proposed system using our customized simulator written in Matlab programing language and comparing its performance with other related works, significant enhancements have been observed in terms of stabilizing the queue lengths at an intersection after solving an emergency case. © 2013 Praise Worthy Prize S.r.l. - All rights reserved.

Item Type: Article
Additional Information: cited By 1
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 09 Nov 2023 15:52
Last Modified: 09 Nov 2023 15:52
URI: https://khub.utp.edu.my/scholars/id/eprint/3937

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