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Most of Automatic Accident Detection Algorithm has a problem of detecting an accident as traffic congestion. Actually, center`s managers deal with accidents depend on watching CCTV or accident report by drivers even though they run the Automatic Accident Detection system. It is because of the system`s detecting errors such as detecting non-accidents as accidents, and it makes decreasing in the system`s overall reliability. It means that Automatic Accident Detection Algorithm should not only have high detection probability but also have low false alarm probability, and it has to detect accurate accident spot. The study tries to verify and evaluate the effectiveness of using Gaussian Mixture Model and individual vehicle tracking to adapt Accident Detection Algorithm to Center Management System by measuring accident detection probability and false alarm probability`s frequency in the real accident.

Measuring of Effectiveness of Tracking Based Accident Detection Algorithm Using Gaussian Mixture Model