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

Principal Investigator:

Eil Kwon, Director, NATSRL, UMD-Civil Engineering

Project Summary:

The capability to accurately and reliably estimate the performance of winter maintenance activities is critical for improving the efficiency and effectiveness of Minnesota Department of Transportation operations. Phase 1 of this research produced a prototype process to estimate the speed variation points during recovery periods for given routes using the traffic flow data collected from field detectors. In this Phase 2 project, the prototype process will be enhanced with the expanded data set and traffic-data-based alternative measures will be developed for snow maintenance operations. The enhanced process will be applied to selected snow events in the metro freeway network to estimate those measures for the selected routes.

Sponsor:

Project Details: