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Dangerous driving event analysis system by a cascaded fuzzy reasoning Petri net

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

Abstract

This study applies a modified cascaded fuzzy reasoning Petri net (CFRPN) model to analyze dangerous driving events on a freeway. The dangerous driving events can be divided into two groups: (1) the interaction between a driver's vehicle and the road environment, and (2) the interaction between a driver's vehicle and nearby vehicles. These two classes of driving events may occur simultaneously and lead to certain serious traffic situations. The proposed system analyzes these two kinds of events determines dangerous situations from data collected by various sensors. Since collecting real driving event data on freeway is dangerous and time consuming, a data generation system is developed to generate the experimental data. Such data can help evaluate the performance of the proposed analysis system. Finally, experimental results show that the proposed system is accurate and robust.

Original languageEnglish
Title of host publicationProceedings of ITSC 2006
Subtitle of host publication2006 IEEE Intelligent Transportation Systems Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages337-342
Number of pages6
ISBN (Print)1424400945, 9781424400942
DOIs
Publication statusPublished - 2006
Event2006 IEEE Intelligent Transportation Systems Conference, ITSC 2006 - Toronto, ON, Canada
Duration: 2006 Sept 172006 Sept 20

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
ISSN (Print)2153-0009
ISSN (Electronic)2153-0017

Conference

Conference2006 IEEE Intelligent Transportation Systems Conference, ITSC 2006
Country/TerritoryCanada
CityToronto, ON
Period2006/09/172006/09/20

Keywords

  • Active driver assistance system
  • Driving event analysis
  • Fuzzy reasoning Petri net

ASJC Scopus subject areas

  • General Engineering

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