Genetic fuzzy logic traffic signal control with cell transmission modeling

Yu-Chiun Chiou*, Yen Fei Huang

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

This study develops an adaptive traffic signal control model based on an iterative genetic fuzzy logic controller (GFLC). The proposed model considers traffic flow and queue length as state variables and extension of green time as control variable, toward the minimization of total vehicle delays. For the learning efficiency of GFLC and the capability in capturing traffic behaviors, cell transmission model is used to replicate the traffic condition. To investigate, the performance of the proposed model in the case of an isolated intersection, comparisons to pretimed signal timing plans determining by Webster and total enumeration methods, and two queue-length based adaptive models are conducted. Results show that our proposed GFLC model performs best. As traffic flows vary more noticeably, the GFLC traffic signal control model performs even better than any timing plans. In the case of sequential intersections with four coordinated signal systems: simultaneous, progressive, alternate, and independent, the experimental example study also show that the proposed GFLC model can also perform better than current and pretimed timing plans, suggesting that the proposed GFLC signal control model is effective, robust, and adaptable.

Original languageEnglish
Pages (from-to)446-460
Number of pages15
JournalJournal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an
Volume37
Issue number4
DOIs
StatePublished - 19 May 2014

Keywords

  • adaptive signal control
  • cell transmission model
  • genetic fuzzy logic controller

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