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International Journal of Electrical and Computer Engineering (IJECE)
Article . 2018 . Peer-reviewed
License: CC BY NC
Data sources: Crossref
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Article . 2018
License: CC BY
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Traffic Light Signal Parameters Optimization using Modification of Multielement Genetic Algorithm

Authors: I Gede Pasek Suta Wijaya; Keeichi Uchimura; Gou Koutaki;

Traffic Light Signal Parameters Optimization using Modification of Multielement Genetic Algorithm

Abstract

A strategy to optimize traffic light signal parameters is presented for solving traffic congestion problem using modification of the Multielement Genetic Algorithm (MEGA). The aim of this method is to improve the lack of vehicle throughput (FF ) of the works called as traffic light signal parameters optimization using the MEGA and Particle Swarm Optimization (PSO). In this case, the modification of MEGA is done by adding Hash-Table for saving some best populations for accelerating the recombination process of MEGA which is shortly called as H-MEGA. The experimental results show that the H-MEGA based optimization provides better performance than MEGA and PSO based methods (improving the FF of both MEGA and PSO based optimization methods by about 10.01% (from 82,63% to 92.64%) and 6.88% (from 85.76% to 92.64%), respectively). In addition, the H-MEGA improve significantly the real FF of Ooe Toroku road network of Kumamoto City, Japan about 21.62%.

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Keywords

Artificial intelligence, transportation system, signal parameters, GA, optimization

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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