Center for Transportation Studies, University of Minnesota
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.
Kwon, Eil; Park, Chongmyung; Hong, Seongah; Jeon, Soobin.
Estimation of Winter Snow Operation Performance Measures with Traffic-Flow Data, Phase 2.
Center for Transportation Studies, University of Minnesota.
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