A traffic accident detection model using metadata registry

Yong Kul Ki, Jin Woo Kim, Doo Kwon Baik

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

9 Citations (Scopus)

Abstract

In this research, we suggested a traffic accident detection model and installed a system for automatically detecting, recording, and reporting traffic accidents at intersections. A system with these properties would be beneficial in determining the cause of accidents and the features of the intersection that impact safety. Additionally, we suggested and designed the metadata registry for the system to improve the interoperability. In a field test, the suggested model achieved a False Alarm Rate (FAR) of 0.34×10 -6 percent. Considering that a California #7a algorithm (expressway incident detection algorithm) showed a FAR of 0.08-0.34 percent, our result is a remarkable achievement.

Original languageEnglish
Title of host publicationProceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006
Pages255-259
Number of pages5
DOIs
Publication statusPublished - 2006
Event4th International Conference on Software Engineering Research, Management and Applications, SERA 2006 - Seattle, WA, United States
Duration: 2006 Aug 92006 Aug 11

Publication series

NameProceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006

Other

Other4th International Conference on Software Engineering Research, Management and Applications, SERA 2006
Country/TerritoryUnited States
CitySeattle, WA
Period06/8/906/8/11

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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