A neuro-fuzzy logic for ATIS stand-alone control systems: Structure, calibration, and analyses

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2 Citations (Scopus)

Abstract

An Advanced Traveler Information System (ATIS) stand-alone operation scheme is formulated as a bi-level optimization problem. The scheme logic attempts to optimize the network overall travel time by adjusting the path proportions while guessing the signal phase split decisions. An approximate simulation-based optimization algorithm is devised as an example of the logic operating this scheme. The logic is then replicated by a fuzzy-logic control system. Neural nets are utilized to develop the knowledge base of the fuzzy system and to calibrate the fuzzy set parameters. The neural nets utilize data replicates generated by the approximate simulation-based optimization algorithm. The calibration and effectiveness results of the fuzzy control system are presented.

Original languageEnglish
Pages (from-to)186-202
Number of pages17
JournalComputer-Aided Civil and Infrastructure Engineering
Volume19
Issue number3
DOIs
Publication statusPublished - May 2004

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics

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