Cover Image

Decentralized traffic signal control for grid traffic network using genetic algorithm

This work aims to explore the potential to minimize traffic congestion using a non-deterministic algorithm. Conventionally, the deterministic algorithm such as fuzzy logic was proposed as the computational algorithm to compute the optimum traffic signal timing for minimizing vehicles in queue and tr...

Full description

Saved in:
Bibliographic Details
Main Authors: Min Keng Tan, Helen Sin Ee Chuo, Kiam Beng Yeo, Renee Ka Yin Chin, Sha Huang, Kenneth Tze Kin Teo
Format: Proceedings
Language:English
English
Published: IEEE 2019
Subjects:
QA75.5-76.95 Electronic computers. Computer science
TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Online Access:https://eprints.ums.edu.my/id/eprint/31463/1/Decentralized%20traffic%20signal%20control%20for%20grid%20traffic%20network%20using%20genetic%20algorithm-ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/31463/2/Decentralized%20traffic%20signal%20control%20for%20grid%20traffic%20network%20using%20genetic%20algorithm.pdf
https://eprints.ums.edu.my/id/eprint/31463/
https://ieeexplore.ieee.org/document/9117490
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.ums.eprints.31463
record_format eprints
spelling my.ums.eprints.314632021-12-22T00:57:16Z https://eprints.ums.edu.my/id/eprint/31463/ Decentralized traffic signal control for grid traffic network using genetic algorithm Min Keng Tan Helen Sin Ee Chuo Kiam Beng Yeo Renee Ka Yin Chin Sha Huang Kenneth Tze Kin Teo QA75.5-76.95 Electronic computers. Computer science TK1-9971 Electrical engineering. Electronics. Nuclear engineering This work aims to explore the potential to minimize traffic congestion using a non-deterministic algorithm. Conventionally, the deterministic algorithm such as fuzzy logic was proposed as the computational algorithm to compute the optimum traffic signal timing for minimizing vehicles in queue and travel delay. However, it is very difficult to define the suitable number of fuzzy rules that are able to cover the all possibilities of traffic flow changes since the natural traffic flow behavior is dynamic. Besides, the inherent deterministic behavior limits the algorithm to explore the solution space in searching for the optimum traffic solution. In other words, the deterministic algorithm will not provide other solution with the same input. Therefore, genetic algorithm, a non-deterministic algorithm, is proposed to optimize the traffic signalization. A benchmarked 3×3 grid traffic network is developed as the testbed to examine the robustness of the proposed GA. Each intersection is integrated with a GA based signal controller or known as agent to form a multi-agent system. Each agent has the autonomy in controlling their own traffic intersection and they will share their local traffic information to their downstream intersections. The performance of the proposed GA is compared with the conventional fuzzy logic. The simulation results show the proposed GA improves the performance about 6.6 % in minimizing vehicles in queue and travel delay as compared to the conventional fuzzy logic. IEEE 2019-12 Proceedings PeerReviewed text en https://eprints.ums.edu.my/id/eprint/31463/1/Decentralized%20traffic%20signal%20control%20for%20grid%20traffic%20network%20using%20genetic%20algorithm-ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/31463/2/Decentralized%20traffic%20signal%20control%20for%20grid%20traffic%20network%20using%20genetic%20algorithm.pdf Min Keng Tan and Helen Sin Ee Chuo and Kiam Beng Yeo and Renee Ka Yin Chin and Sha Huang and Kenneth Tze Kin Teo (2019) Decentralized traffic signal control for grid traffic network using genetic algorithm. https://ieeexplore.ieee.org/document/9117490
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA75.5-76.95 Electronic computers. Computer science
TK1-9971 Electrical engineering. Electronics. Nuclear engineering
spellingShingle QA75.5-76.95 Electronic computers. Computer science
TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Min Keng Tan
Helen Sin Ee Chuo
Kiam Beng Yeo
Renee Ka Yin Chin
Sha Huang
Kenneth Tze Kin Teo
Decentralized traffic signal control for grid traffic network using genetic algorithm
description This work aims to explore the potential to minimize traffic congestion using a non-deterministic algorithm. Conventionally, the deterministic algorithm such as fuzzy logic was proposed as the computational algorithm to compute the optimum traffic signal timing for minimizing vehicles in queue and travel delay. However, it is very difficult to define the suitable number of fuzzy rules that are able to cover the all possibilities of traffic flow changes since the natural traffic flow behavior is dynamic. Besides, the inherent deterministic behavior limits the algorithm to explore the solution space in searching for the optimum traffic solution. In other words, the deterministic algorithm will not provide other solution with the same input. Therefore, genetic algorithm, a non-deterministic algorithm, is proposed to optimize the traffic signalization. A benchmarked 3×3 grid traffic network is developed as the testbed to examine the robustness of the proposed GA. Each intersection is integrated with a GA based signal controller or known as agent to form a multi-agent system. Each agent has the autonomy in controlling their own traffic intersection and they will share their local traffic information to their downstream intersections. The performance of the proposed GA is compared with the conventional fuzzy logic. The simulation results show the proposed GA improves the performance about 6.6 % in minimizing vehicles in queue and travel delay as compared to the conventional fuzzy logic.
format Proceedings
author Min Keng Tan
Helen Sin Ee Chuo
Kiam Beng Yeo
Renee Ka Yin Chin
Sha Huang
Kenneth Tze Kin Teo
author_facet Min Keng Tan
Helen Sin Ee Chuo
Kiam Beng Yeo
Renee Ka Yin Chin
Sha Huang
Kenneth Tze Kin Teo
author_sort Min Keng Tan
title Decentralized traffic signal control for grid traffic network using genetic algorithm
title_short Decentralized traffic signal control for grid traffic network using genetic algorithm
title_full Decentralized traffic signal control for grid traffic network using genetic algorithm
title_fullStr Decentralized traffic signal control for grid traffic network using genetic algorithm
title_full_unstemmed Decentralized traffic signal control for grid traffic network using genetic algorithm
title_sort decentralized traffic signal control for grid traffic network using genetic algorithm
publisher IEEE
publishDate 2019
url https://eprints.ums.edu.my/id/eprint/31463/1/Decentralized%20traffic%20signal%20control%20for%20grid%20traffic%20network%20using%20genetic%20algorithm-ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/31463/2/Decentralized%20traffic%20signal%20control%20for%20grid%20traffic%20network%20using%20genetic%20algorithm.pdf
https://eprints.ums.edu.my/id/eprint/31463/
https://ieeexplore.ieee.org/document/9117490
_version_ 1760230896091267072
score 13.211869

Similar Items