Estimation of Winter Snow Operation Performance Measures with Traffic Flow Data

Principal Investigator(s):

Eil Kwon, Professor, UMD-Civil Engineering

Project summary:

This research produced an automatic process to identify the road condition recovery times during snow events from traffic-flow data. For this study, traffic data from past snow events were analyzed and the speed variation patterns indicating the road condition recovery states during the recovery periods were identified. The prototype process developed finds the speed-change point indicating recovery of the road condition by analyzing speed variations for a given location. The process was then applied to a set of past snow events and the estimated recovered times were compared with the reported lane-regain time data.

Project details: