A traffic accident detection model using metadata registry

Yong Kul Ki; Jin Woo Kim; Doo Kwon Baik

doi:10.1109/SERA.2006.8

A traffic accident detection model using metadata registry

Yong Kul Ki^*
, Jin Woo Kim
, Doo Kwon Baik

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 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 language	English
Title of host publication	Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006
Pages	255-259
Number of pages	5
DOIs	https://doi.org/10.1109/SERA.2006.8
Publication status	Published - 2006
Event	4th International Conference on Software Engineering Research, Management and Applications, SERA 2006 - Seattle, WA, United States Duration: 2006 Aug 9 → 2006 Aug 11

Publication series

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

Other

Other	4th International Conference on Software Engineering Research, Management and Applications, SERA 2006
Country/Territory	United States
City	Seattle, WA
Period	06/8/9 → 06/8/11

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

ASJC Scopus subject areas

Computer Science Applications
Software

Access to Document

10.1109/SERA.2006.8

Cite this

Ki, Y. K., Kim, J. W., & Baik, D. K. (2006). A traffic accident detection model using metadata registry. In Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006 (pp. 255-259). Article 1691389 (Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006). https://doi.org/10.1109/SERA.2006.8

A traffic accident detection model using metadata registry. / Ki, Yong Kul; Kim, Jin Woo; Baik, Doo Kwon.
Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006. 2006. p. 255-259 1691389 (Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ki, YK, Kim, JW & Baik, DK 2006, A traffic accident detection model using metadata registry. in Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006., 1691389, Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006, pp. 255-259, 4th International Conference on Software Engineering Research, Management and Applications, SERA 2006, Seattle, WA, United States, 06/8/9. https://doi.org/10.1109/SERA.2006.8

Ki YK, Kim JW, Baik DK. A traffic accident detection model using metadata registry. In Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006. 2006. p. 255-259. 1691389. (Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006). doi: 10.1109/SERA.2006.8

@inproceedings{3acc94550e5340b7ad5613897bc6d296,

title = "A traffic accident detection model using metadata registry",

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.",

author = "Ki, \{Yong Kul\} and Kim, \{Jin Woo\} and Baik, \{Doo Kwon\}",

note = "Copyright: Copyright 2011 Elsevier B.V., All rights reserved.; 4th International Conference on Software Engineering Research, Management and Applications, SERA 2006 ; Conference date: 09-08-2006 Through 11-08-2006",

year = "2006",

doi = "10.1109/SERA.2006.8",

language = "English",

isbn = "076952656X",

series = "Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006",

pages = "255--259",

booktitle = "Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006",

}

TY - GEN

T1 - A traffic accident detection model using metadata registry

AU - Ki, Yong Kul

AU - Kim, Jin Woo

AU - Baik, Doo Kwon

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/34547264486

UR - https://www.scopus.com/pages/publications/34547264486#tab=citedBy

U2 - 10.1109/SERA.2006.8

DO - 10.1109/SERA.2006.8

M3 - Conference contribution

AN - SCOPUS:34547264486

SN - 076952656X

SN - 9780769526560

T3 - Proceedings - Fourth International Conference on Software Engineering Research, Management and Applications, SERA 2006

SP - 255

EP - 259

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

T2 - 4th International Conference on Software Engineering Research, Management and Applications, SERA 2006

Y2 - 9 August 2006 through 11 August 2006

ER -

A traffic accident detection model using metadata registry

Abstract

Publication series

Other

UN SDGs

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this