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

    13 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

    Fingerprint

    Dive into the research topics of 'A traffic accident detection model using metadata registry'. Together they form a unique fingerprint.

    Cite this