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

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 a...

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Main Authors: Turky A.M., Ahmad M.S., Yusoff M.Z.M., Hammad B.T.
Other Authors: 25825717300
Format: Conference paper
Published: 2023
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spelling my.uniten.dspace-308732023-12-29T15:55:06Z Using genetic algorithm for traffic light control system with a pedestrian crossing Turky A.M. Ahmad M.S. Yusoff M.Z.M. Hammad B.T. 25825717300 7402895985 22636590200 57193327622 Cellular Automata Genetic Algorithm Traffic Control Systems Cellular automata Control system analysis Control systems Controllers Crossings (pipe and cable) Dynamical systems Footbridges Fuzzy sets Genetic algorithms Light transmission Pattern recognition systems Pedestrian safety Rough set theory Traffic control Translation (languages) Vehicles Dynamic Systems Green light Number of vehicles Pedestrian crossing Performance comparison Red light Time control Time controller Traffic light Traffic light control systems Two-lane traffic Genetic engineering 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. � 2009 Springer Berlin Heidelberg. Final 2023-12-29T07:55:06Z 2023-12-29T07:55:06Z 2009 Conference paper 10.1007/978-3-642-02962-2_65 2-s2.0-69049111101 https://www.scopus.com/inward/record.uri?eid=2-s2.0-69049111101&doi=10.1007%2f978-3-642-02962-2_65&partnerID=40&md5=576f90f235b915b0cf0993d25b3a891c https://irepository.uniten.edu.my/handle/123456789/30873 5589 LNAI 512 519 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Cellular Automata
Genetic Algorithm
Traffic Control Systems
Cellular automata
Control system analysis
Control systems
Controllers
Crossings (pipe and cable)
Dynamical systems
Footbridges
Fuzzy sets
Genetic algorithms
Light transmission
Pattern recognition systems
Pedestrian safety
Rough set theory
Traffic control
Translation (languages)
Vehicles
Dynamic Systems
Green light
Number of vehicles
Pedestrian crossing
Performance comparison
Red light
Time control
Time controller
Traffic light
Traffic light control systems
Two-lane traffic
Genetic engineering
spellingShingle Cellular Automata
Genetic Algorithm
Traffic Control Systems
Cellular automata
Control system analysis
Control systems
Controllers
Crossings (pipe and cable)
Dynamical systems
Footbridges
Fuzzy sets
Genetic algorithms
Light transmission
Pattern recognition systems
Pedestrian safety
Rough set theory
Traffic control
Translation (languages)
Vehicles
Dynamic Systems
Green light
Number of vehicles
Pedestrian crossing
Performance comparison
Red light
Time control
Time controller
Traffic light
Traffic light control systems
Two-lane traffic
Genetic engineering
Turky A.M.
Ahmad M.S.
Yusoff M.Z.M.
Hammad B.T.
Using genetic algorithm for traffic light control system with a pedestrian crossing
description 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. � 2009 Springer Berlin Heidelberg.
author2 25825717300
author_facet 25825717300
Turky A.M.
Ahmad M.S.
Yusoff M.Z.M.
Hammad B.T.
format Conference paper
author Turky A.M.
Ahmad M.S.
Yusoff M.Z.M.
Hammad B.T.
author_sort Turky A.M.
title Using genetic algorithm for traffic light control system with a pedestrian crossing
title_short Using genetic algorithm for traffic light control system with a pedestrian crossing
title_full Using genetic algorithm for traffic light control system with a pedestrian crossing
title_fullStr Using genetic algorithm for traffic light control system with a pedestrian crossing
title_full_unstemmed Using genetic algorithm for traffic light control system with a pedestrian crossing
title_sort using genetic algorithm for traffic light control system with a pedestrian crossing
publishDate 2023
_version_ 1806424081234395136
score 13.214268