Researchers at the University of Minnesota Duluth (UMD) have developed a system that can use highway loop detector traffic flow and weather data to determine when road conditions have recovered from a snow event. Currently, the Minnesota Department of Transportation (MnDOT) relies on snowplow drivers to estimate when roads are back to normal. The new system aims to relieve drivers of that burden and increase overall fleet efficiency.
In two previous MnDOT-funded projects, UMD researchers looked at using data from loop detectors along with weather station data to develop an automated system that determines normal condition regain time (NCRT) based on changes in traffic flow patterns. The goal is to improve the accuracy of road condition estimates and give dispatchers a big-picture view of traffic flow.