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Associate Director of External Affairs | Cheryl Reitan | creitan@d.umn.edu | (218) 726-8996
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March 5, 2013
Eil Kwon | Director, NATSRL | 218 726-6452 | eilkwon@d.umn.edu
Steve Lund | MnDOT | 651 366-3566 | steven.lund@state.mn.us
Cheryl Reitan | Associate Director of External Affairs | 218 726-8996 | creitan@d.umn.edu


UMD/MnDOT Study of Winter Storm Traffic and Road Recovery

DULUTH, MN The first phase of a research project led by UMD Civil Engineering Professor Eil Kwon and sponsored by the Minnesota Department of Transportation (MnDOT) looks at traffic data to more accurately and reliably determine snow management performance and road recovery time.

The methodology takes data on traffic speed, flow, and density to estimate at what time traffic patterns return to normal. This information can be used by MnDOT to help determine plowing performance. According to MnDOT State Maintenance Engineer Steve Lund, MnDOT now relies on visual observations from snow fighters (snow plow drivers) and supervisors to determine if performance goals are being met. "If successful, the tool being developed by UMD will automate performance reporting and recording," said Lund. "This will address any concern of subjectivity. The tool could also remove the task of recording plowing performance away from snow fighters, allowing them to concentrate on plowing efforts. "

Kwon began the project by identifying two common patterns after a snowfall, speed recovery affected by road condition only and speed recovery affected by road conditions and traffic flow. Based on those patterns, he developed a prototype to determine road condition recovery time by examining the speed change rates and the amount of traffic flow on a given roadway after snow ends. When the prototype factored in traffic flow, such as traffic density during rush hour, it determined that speeds might not reach normal levels even with clear roads.

The prototype procedure was tested by Kwon with the data collected from two snow removal routes in the Twin Cities during 2011. "The test results are promising in terms of identifying speed changes and road recovery times," Kwon said. The second phase of the UMD/MnDOT project is currently underway. Researchers are refining their prototype, so it can more accurately identify flow recovery patterns under different snowfall conditions.



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