A simulation-based fuzzy model for traffic signal control

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Fuzzy logic has been recognized in the literature as an effective methodology for real-time signal control. The majority of the fuzzy controllers in the literature depend on simple logic that particularly depends on raw data of a single detector. Their input variables are usually simple estimates of traffic measures such as flow, speed or occupancy, estimated from such single detector readings. A room for improvement is sought in this paper by developing a fuzzy logic model (FLM) that could be integrated with smarter "processing" tools to estimate several traffic measures from multiple detectors on each approach. The estimates obtained from this processing tool are integrated as input knowledge into the FLM. The mathematical formulation of these traffic measures is presented. The fuzzy logic structure is addressed in details. A simulation model is devised to test the effectiveness of the FLM. The results are presented and discussed in details.

Original languageEnglish
Title of host publicationProceedings of the 4th WSEAS International Conference on Computational Intelligence, CI '10
Pages113-121
Number of pages9
Publication statusPublished - Dec 1 2010
Event4th WSEAS International Conference on Computational Intelligence, CI '10 - Bucharest, Romania
Duration: Apr 20 2010Apr 22 2010

Publication series

NameProceedings of the 4th WSEAS International Conference on Computational Intelligence, CI '10

Conference

Conference4th WSEAS International Conference on Computational Intelligence, CI '10
Country/TerritoryRomania
CityBucharest
Period4/20/104/22/10

Keywords

  • Detectors
  • Fuzzy logic model
  • Real-time
  • Simulation
  • Traffic control
  • Traffic measures

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics

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