Using genetic algorithm for traffic light control system with a pedestrian crossing

Ayad M. Turky, M. S. Ahmad, Mohd Zaliman Mohd Yusoff, Baraa T. Hammad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

In this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better.

Original languageEnglish
Title of host publicationRough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings
Pages512-519
Number of pages8
DOIs
Publication statusPublished - 27 Aug 2009
Event4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009 - Gold Coast, QLD, Australia
Duration: 14 Jul 200916 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5589 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009
CountryAustralia
CityGold Coast, QLD
Period14/07/0916/07/09

Fingerprint

Crosswalks
Telecommunication traffic
Genetic algorithms
Control System
Traffic
Genetic Algorithm
Control systems
Controller
Controllers
Red Light
Performance Comparison
Dynamic Systems
Queue
Resolve
Dynamical systems
Monitor
Optimise

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Turky, A. M., Ahmad, M. S., Mohd Yusoff, M. Z., & Hammad, B. T. (2009). Using genetic algorithm for traffic light control system with a pedestrian crossing. In Rough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings (pp. 512-519). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5589 LNAI). https://doi.org/10.1007/978-3-642-02962-2_65
Turky, Ayad M. ; Ahmad, M. S. ; Mohd Yusoff, Mohd Zaliman ; Hammad, Baraa T. / Using genetic algorithm for traffic light control system with a pedestrian crossing. Rough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings. 2009. pp. 512-519 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{57f728688e244442838e66f61ff63b4c,
title = "Using genetic algorithm for traffic light control system with a pedestrian crossing",
abstract = "In this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better.",
author = "Turky, {Ayad M.} and Ahmad, {M. S.} and {Mohd Yusoff}, {Mohd Zaliman} and Hammad, {Baraa T.}",
year = "2009",
month = "8",
day = "27",
doi = "10.1007/978-3-642-02962-2_65",
language = "English",
isbn = "3642029612",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "512--519",
booktitle = "Rough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings",

}

Turky, AM, Ahmad, MS, Mohd Yusoff, MZ & Hammad, BT 2009, Using genetic algorithm for traffic light control system with a pedestrian crossing. in Rough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5589 LNAI, pp. 512-519, 4th International Conference on Rough Sets and Knowledge Technology, RSKT 2009, Gold Coast, QLD, Australia, 14/07/09. https://doi.org/10.1007/978-3-642-02962-2_65

Using genetic algorithm for traffic light control system with a pedestrian crossing. / Turky, Ayad M.; Ahmad, M. S.; Mohd Yusoff, Mohd Zaliman; Hammad, Baraa T.

Rough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings. 2009. p. 512-519 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5589 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Using genetic algorithm for traffic light control system with a pedestrian crossing

AU - Turky, Ayad M.

AU - Ahmad, M. S.

AU - Mohd Yusoff, Mohd Zaliman

AU - Hammad, Baraa T.

PY - 2009/8/27

Y1 - 2009/8/27

N2 - In this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better.

AB - In this paper, we explore the use of genetic algorithm and implementing the technology to improve the performance of traffic light and pedestrian crossing control in a four-way, two-lane traffic junction. The algorithm resolves the limitations of traditional fixed-time control for passing vehicles and pedestrians. It employs a dynamic system to control the traffic light and pedestrian crossing that monitors two sets of parameters: the vehicle and pedestrian queues behind a red light and the number of vehicles and pedestrians that passes through a green light. The algorithm dynamically optimizes the red and green times to control the flow of both the vehicles and the pedestrians. Performance comparisons between the genetic algorithm controller and a fixed-time controller reveal that the genetic algorithm controller performs significantly better.

UR - http://www.scopus.com/inward/record.url?scp=69049111101&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=69049111101&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-02962-2_65

DO - 10.1007/978-3-642-02962-2_65

M3 - Conference contribution

SN - 3642029612

SN - 9783642029615

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 512

EP - 519

BT - Rough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings

ER -

Turky AM, Ahmad MS, Mohd Yusoff MZ, Hammad BT. Using genetic algorithm for traffic light control system with a pedestrian crossing. In Rough Sets and Knowledge Technology - 4th International Conference, RSKT 2009, Proceedings. 2009. p. 512-519. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-02962-2_65