Incident Detection in Freeway Based on Autocorrelation Factor of GPS Probe Data.

This study proposes a statistical approach to incident detection in a section of the intercity freeway by applying GPS probe data to a GIS geofenced platform. We evaluated the proposed method using data sources from real traffic sensors of the intercity Tehran-Qom freeway in Iran. Through the SEPEHTAN project in Iran, intercity bus fleet equipped with an onboard unit that provides GPS data transferring to the central database. The main novelties in this paper are gathering density and speed time series from GPS probe data in a GIS platform and using autocorrelation factor to detect the location of the incident. The method compared with three different AID algorithms and real terms as well. Although the penetration rate was 3%, the results were considerably meet with the actual traffic condition. We reached 92.8% detection rate and 7.1% for the false alarm. [ABSTRACT FROM AUTHOR]