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http://dx.doi.org/10.12815/kits.2016.15.2.013

Development of an AIDA(Automatic Incident Detection Algorithm) for Uninterrupted Flow Based on the Concept of Short-term Displaced Flow  

Lee, Kyu-Soon (DongRim TNS)
Shin, Chi-Hyun (Kyonggi University)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.15, no.2, 2016 , pp. 13-23 More about this Journal
Abstract
Many traffic centers are highly hesitant in employing existing Automatic Incident Detection Algorithms due to high false alarm rate, low detection rate, and enormous effort taken in maintaining algorithm parameters, together with complex algorithm structure and filtering/smoothing process. Concerns grow over the situation particularly in Freeway Incident Management Area This study proposes a new algorithm and introduces a novel concept, the Displaced Flow Index (DiFI) which is similar to a product of relative speed and relative occupancy for every execution period. The algorithm structure is very simple, also easy to understand with minimum parameters, and could use raw data without any additional pre-processing. To evaluate the performance of the DiFI algorithm, validation test on the algorithm has been conducted using detector data taken from Naebu Expressway in Seoul and following transferability tests with Gyeongbu Expressway detector data. Performance test has utilized many indices such as DR, FAR, MTTD (Mean Time To Detect), CR (Classification Rate), CI (Composite Index) and PI (Performance Index). It was found that the DR is up to 100%, the MTTD is a little over 1.0 minutes, and the FAR is as low as 2.99%. This newly designed algorithm seems promising and outperformed SAO and most popular AIDAs such as APID and DELOS, and showed the best performance in every category.
Keywords
Automatic incident detection algorithm; DR; FAR; MTTD; PI;
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