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Traffic Flow Maximization using Evolutionary Algorithm

by Cui Jiaxing, Quentin De Metz
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 101 - Number 5
Year of Publication: 2014
Authors: Cui Jiaxing, Quentin De Metz
10.5120/17680-8514

Cui Jiaxing, Quentin De Metz . Traffic Flow Maximization using Evolutionary Algorithm. International Journal of Computer Applications. 101, 5 ( September 2014), 1-6. DOI=10.5120/17680-8514

@article{ 10.5120/17680-8514,
author = { Cui Jiaxing, Quentin De Metz },
title = { Traffic Flow Maximization using Evolutionary Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { September 2014 },
volume = { 101 },
number = { 5 },
month = { September },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-6 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume101/number5/17680-8514/ },
doi = { 10.5120/17680-8514 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:30:52.196125+05:30
%A Cui Jiaxing
%A Quentin De Metz
%T Traffic Flow Maximization using Evolutionary Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 101
%N 5
%P 1-6
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Traffic Flow maximization is one of the crucial problems in designing a city. It directly affects the daily life of the people living in that city. It is a complex problem, one that in most cases cannot be deterministically solved. This paper proposes using evolutionary algorithms to solve that problem. This paper compares existing work and traffic flow with solutions yielded by evolutionary approach, and the results show that it is beneficial to adopt this strategy when designing traffic light timings.

References
  1. Wolfgang Banzhaf, Peter Nordin, Robert E Keller, and Frank D Francone. Genetic programming: an introduction, volume 1. Morgan Kaufmann San Francisco, 1998.
  2. Agoston E Eiben and James E Smith. Introduction to evolutionary computing. springer, 2003.
  3. Gustaf Jansson. Traffic control with standard genetic algorithm, 2010.
  4. Daniel Krajzewicz, Jakob Erdmann, Michael Behrisch, and Laura Bieker. Recent development and applications of SUMO - Simulation of Urban MObility. International Journal On Advances in Systems and Measurements, 5(3&4):128–138, December 2012.
  5. Javier J Sanchez Medina. Evolutionary computation applied to urban traffic optimization, 2008.
  6. Peter JM Van Laarhoven and Emile HL Aarts. Simulated annealing. Springer, 1987.
  7. Michael D Vose. The simple genetic algorithm: foundations and theory, volume 12. MIT press, 1999.
  8. Ken Walters. Smart traffic signals pilot results: Pollution plunges, traffic clogs cleared, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Evolutionary Algorithm Traffic Light Optimization FTGA MTGA

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