A fuzzy logic model for real-time incident detection in urban road network

Faisal Ahmed, Yaser E. Hawas

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

11 Citations (Scopus)

Abstract

Incident detection systems for the urban traffic network are still lacking efficient algorithms or models for better performance. This paper presents a new urban incident detection system based on the application of Fuzzy Logic modeling. Offline urban incident and corresponding non-incident scenarios are generated using a microscopic simulation model assuming varying traffic link flows, phase timing, cycle times, and link lengths. The traffic measures are extracted from three detectors on each link. Statistical significance analysis was utilized to identify the significant input variables to be used in developing the Neuro-fuzzy model. A set of data was generated and used for training of the proposed Neuro-fuzzy model, while another set was used for validation. The performance of the proposed model is assessed using the success and the false alarm rates of detecting an incident at a specific cycle time.

Original languageEnglish
Title of host publicationICAART 2013 - Proceedings of the 5th International Conference on Agents and Artificial Intelligence
Pages465-472
Number of pages8
Publication statusPublished - 2013
Event5th International Conference on Agents and Artificial Intelligence, ICAART 2013 - Barcelona, Spain
Duration: Feb 15 2013Feb 18 2013

Publication series

NameICAART 2013 - Proceedings of the 5th International Conference on Agents and Artificial Intelligence
Volume2

Other

Other5th International Conference on Agents and Artificial Intelligence, ICAART 2013
Country/TerritorySpain
CityBarcelona
Period2/15/132/18/13

Keywords

  • Average speed
  • Detection rate
  • Detector count
  • False alarm rate
  • Fuzzy logic and systems
  • Intelligent transport system
  • Neuro-fuzzy
  • Urban incident detection

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'A fuzzy logic model for real-time incident detection in urban road network'. Together they form a unique fingerprint.

Cite this