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A Signal Timing Optimization in Traffic Management using ABC Algorithm

by R. Subashini, A. R. Rishivarman
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 165 - Number 1
Year of Publication: 2017
Authors: R. Subashini, A. R. Rishivarman
10.5120/ijca2017913786

R. Subashini, A. R. Rishivarman . A Signal Timing Optimization in Traffic Management using ABC Algorithm. International Journal of Computer Applications. 165, 1 ( May 2017), 35-39. DOI=10.5120/ijca2017913786

@article{ 10.5120/ijca2017913786,
author = { R. Subashini, A. R. Rishivarman },
title = { A Signal Timing Optimization in Traffic Management using ABC Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 165 },
number = { 1 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume165/number1/27541-2017913786/ },
doi = { 10.5120/ijca2017913786 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:11:15.405042+05:30
%A R. Subashini
%A A. R. Rishivarman
%T A Signal Timing Optimization in Traffic Management using ABC Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 165
%N 1
%P 35-39
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The ABC algorithm is a new population-based meta-heuristic approach, and it is inspired by the foraging behaviour of honeybee swarm. This study discusses Artificial Bee Colony (ABC) algorithm for finding optimal setting of traffic signals in coordinated signalized networks for given fixed set of link flows. For optimizing traffic signal timings in coordinated signalized networks, ABC with GA (ABCGA) model is developed and tested. A standard traffic model is used to estimate total network performance index (PI). The ABCGA is tested in various levels with signalized road network. Results showed that the proposed model is slightly better in signal timing optimization in terms of final values of PI when it is compared with Fixed time model, and evolutionary algorithm (EA) based model. Results also showed that the ABCGA model improves network’s PI when it is compared with Fixed time and EA methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Bee Colony Genetic Algorithm signal timings optimization.

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