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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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 |
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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 |
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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 |
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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. |
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25825717300 |
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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. |
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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 |
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13.214268 |