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

C. Y. Fang, H. L. Hsueh, S. W. Chen

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

4 Citations (Scopus)

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: 2006 IEEE Intelligent Transportation Systems Conference
Pages337-342
Number of pages6
Publication statusPublished - 2006
EventITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference - Toronto, ON, Canada
Duration: 2006 Sep 172006 Sep 20

Other

OtherITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference
CountryCanada
CityToronto, ON
Period06/9/1706/9/20

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Keywords

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

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Fang, C. Y., Hsueh, H. L., & Chen, S. W. (2006). Dangerous driving event analysis system by a cascaded fuzzy reasoning Petri net. In Proceedings of ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference (pp. 337-342). [1706764]