Enhanced scheduling traffic light model using discrete event simulation for improved signal timing analysis

Zainal Abidin, Zaheera and Abal Abas, Zuraida and Lim, Ee Theng and Abdul Rahman, Ahmad Fadzli Nizam and Shibghatullah, Abdul Samad (2015) Enhanced scheduling traffic light model using discrete event simulation for improved signal timing analysis. ARPN Journal Of Engineering And Applied Sciences, 10 (18). pp. 8135-8140. ISSN 1819-6608

[img] Text
Enhanced Scheduling Traffic Light Model using DES for Improved Signal Timing.pdf

Download (808kB)

Abstract

Most traffic light today used pre-timed traffic light, traffic light using sensors and traffic light which displaying a countdown timer. However, the existing methods consume a long time of vehicle queuing and waiting the traffic light signals to change, which created congestion at intersection of roads. In this paper, the proposed model enhanced the scheduling traffic light, which simulates the vehicle behaviour based on discrete event simulation and queue theory. Therefore, the simulation becomes more realistic and contributes to accurate outcome. This work focuses on the analysis of the average waiting time for the vehicle in three cases: heavy, medium and low traffic volume. The most optimum traffic signal timing is the one with minimum waiting time for the vehicles. Moreover, the new model solves the critical traffic congestion problem not only in simulation but also in real environment, which drivers take the longest average waiting time is 86 seconds while the shortest average waiting time is 64 seconds at the junction although in heavy traffic congestion. An extensive simulations have been conducted in this work in which a green interval as a control parameter is selected.

Item Type: Article
Uncontrolled Keywords: Traffic light schedulling, Simulation and modelling, Intelligent system, Discrete event simulation
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Information and Communication Technology > Department of Industrial Computing
Depositing User: Dr. Zuraida Abal Abas
Date Deposited: 20 Sep 2017 08:49
Last Modified: 26 Jun 2023 14:54
URI: http://eprints.utem.edu.my/id/eprint/19297
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item