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Evaluation of Texas Incident Detection Algorithm after Years of Implementation

Khaled Hamad and Maher Omar
Department of Civil & Environmental Engineering, University of Sharjah, Sharjah, United Arab Emirates
Abstract—This paper summarizes a performance evaluation of the automatic incident detection algorithm deployed by many traffic management centers across the State of Texas, USA after a few years of implementation in the field. This analysis is the first step towards improving performance of incident detection which will eventually help optimizing freeway incident management practices at these TMCs. To conduct this analysis, the researchers used archived ITS data, particularly freeway incident alarms and incident scenarios data, as well as a geodatabase of ITS features. Matching alarm and scenario data enabled the determination of two performance measures: incident detection rates and false alarm rates. While many researchers evaluated the performance of their proposed incident detection algorithms, only a few assessed the actual performance of these algorithms after long period of implementation. Although the analysis described in this paper uses data from one jurisdiction (San Antonio, Texas), the methodology is sufficiently generic to enable implementation at other traffic management centers.

Index Terms—automatic incident detection algorithm, Texas incident detection algorithm, performance evaluation, detection rate, false alarm rate, TransGuide

Cite: Khaled Hamad and Maher Omar, "Evaluation of Texas Incident Detection Algorithm after Years of Implementation ," Journal of Traffic and Logistics Engineering, Vol. 1, No. 2, pp. 249-253,  December 2013. doi: 10.12720/jtle.1.2.249-253
  
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