Multi-objective optimization of intersection signal time based on genetic algorithm

Mingwei Liu, Yoshinao Oeda, Tomonori Sumi

Research output: Contribution to journalArticle

Abstract

A signal control intersection increases not only vehicle delay, but also capacity reduction in that area. Because more and more fuel and air pollution problems arise recently, an intersection signal control optimization method which aims at reducing vehicle delay, improving capacity is required heavily. This paper proposed a signal control multi-object optimization method to reduce vehicle delay and improve intersection capacity simultaneously at an intersection by using the Genetic Algorithm (GA). Data regarding traffic stream parameters, signal timing details and delay to vehicles are collected from an intersection in Shanghai, Hu Cheng Huan road. The result of the case study shows the optimal timing scheme obtained from this method is better than the observed one.

Original languageEnglish
Pages (from-to)14-23
Number of pages10
JournalMemoirs of the Faculty of Engineering, Kyushu University
Volume78
Issue number4
Publication statusPublished - Dec 12 2018

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Multiobjective optimization
genetic algorithm
Genetic algorithms
Air pollution
atmospheric pollution
road
vehicle
Multi-objective optimization
Genetic algorithm
method

All Science Journal Classification (ASJC) codes

  • Energy(all)
  • Atmospheric Science
  • Earth and Planetary Sciences(all)
  • Management of Technology and Innovation

Cite this

Multi-objective optimization of intersection signal time based on genetic algorithm. / Liu, Mingwei; Oeda, Yoshinao; Sumi, Tomonori.

In: Memoirs of the Faculty of Engineering, Kyushu University, Vol. 78, No. 4, 12.12.2018, p. 14-23.

Research output: Contribution to journalArticle

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