Estimation of Winter Snow Operation Performance Measures with Traffic-Flow Data, Phase 2

Abstract

An automatic process is developed to determine the normal condition regain time (NCRT) using the traffic flow data for a given snow event. To reflect the different traffic flow behavior during day and night time periods, two types of the normal conditions are defined for each detector station. The normal condition for day time is defined with the average speed-density patterns under dry weather conditions, while the time-dependent average speed patterns are used for representing night time periods. In particular, the speed-density functions for the speed recovery and reduction periods were calibrated separately for a given location to address the well-known traffic hysteresis phenomenon. The resulting NCRT estimation process determines the NCRT as the time when the speed level on a given snow day recovers to the target level of the normal recovery speed at the corresponding density for the day time periods. The sample application results with the snow routes in Twin Cities, Minnesota, show the promising possibilities for the estimated NCRT values to be used as the reliable operational measures, which could address the subjectivity and inconsistency issues associated with the current bare-lane regain times determined through visual inspections.