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A Traffic Accident Recording and Reporting Model at Intersections
188 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 8, NO. 2, JUNE 2007
A Traffic Accident Recording and Reporting
Model at Intersections
Yong-Kul Ki, Member, IEEE, and Dong-Young Lee
Abstract—In this paper, we suggested a vision-based traffic
accident detection algorithm and developed a system for auto-
matically 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 an intersec-
tion that impact safety. This model first extracts the vehicles from
the video image of the charge-couple-device camera, tracks the
moving vehicles (MVs), and extracts features such as the variation
rate of the velocity, position, area, and direction of MVs. The
model then makes decisions on the traffic accident based on the
extracted features. In a field test, the suggested model achieved a
correct detection rate (CDR) of 50% and a detection rate of 60%.
Considering that a sound-based accident detection system showed
a CDR of 1% and a DR of 66.1%, our result is a remarkable
achievement.
Index Terms—Accident detection at an intersection, accident
recording and reporting system (ARRS), moving picture, traffic
accident at an intersection, vehicle tracking.
I. INTRODUCTION
EVERY year, vehicular accidents cause tragic loss of lives,cost many countries tremendous amount of money, and
produce substantial congestion to a nation’s transportation sys-
tem. Approximately 50%–60% of the delays on urban freeways
are associated with incidents, and on urban surface streets, a
large percentage of traffic accidents and most delays occur at
or near intersections [1]. Intersections are a common place for
crashes, which may be due to the fact that there are several
conflicting movements, as well as a myriad of different intersec-
tion design characteristics. Intersections also tend to experience
severe crashes due to the fact that several types of injurious
crashes, such
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