A fuzzy logic modeling approach to assess the speed limit suitability in urban street networks

Yaser E. Hawas, Md Bayzid Khan

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

Abstract

This paper discusses the development of fuzzy logic model for estimating the 85th percentile speed of urban roads. Spot speed survey was conducted on four randomly selected urban road segments for a typical weekday and a weekend. The considered road segment attribute data are length of the road segment, number of access points/intersecting links, number of pedestrian crossings, number of lanes, hourly traffic volume, hourly pedestrian volume and current posted speed limits of the selected roads. Such attribute data were collected and used as input variables in the model. Two models for weekday and weekend were developed based on the field survey data. Both models were calibrated using the neuro-fuzzy technique for optimizing the fuzzy logic model (FLM) parameters. Analyses of estimated results show that the FLM can estimate the 85th percentile speed to a reasonable level.

Original languageEnglish
Title of host publicationAgents and Artificial Intelligence
Subtitle of host publication4th International Conference, ICAART 2012 Vilamoura, Portugal, February 6-8, 2012 Revised Selected Papers
PublisherSpringer Verlag
Pages54-68
Number of pages15
ISBN (Print)9783642369063
DOIs
Publication statusPublished - 2013

Publication series

NameCommunications in Computer and Information Science
Volume358
ISSN (Print)1865-0929

Keywords

  • Fuzzy Logic
  • Neuro-fuzzy Training
  • Posted Speed Limit

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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