Improving Traffic Safety through Better Snow Fences: Image-Based Methods to Measure Trapped Snow Volume and the Snow Relocation Coefficient

Project status

Completed

Start date: 08/01/15
End date: 06/30/17

Researcher(s)

Principal investigator:

Co-principal investigators:

About the research

Blowing and drifting snow is a major concern in terms of safety, transportation efficiency, and road maintenance and repair. One common way to mitigate snow drift on roadways is to install structural or living snow fences, but the design of snow fences relies on empirical relationships—in particular, for estimating the snow relocation coefficient (SRC)—that do not necessarily apply to the US Midwest. Therefore, the use of these relationships at sites with different meteorological conditions is problematic.

Moreover, the SRC is a function of the site terrain and ground surface characteristics. Estimating the SRC requires quantification of the snowfall and snow drift fluxes at the site where the snow fence is to be installed. Without being able to estimate the local value of the SRC, an efficient design for the snow fence is practically impossible.

The research described in this report addressed three critical aspects of snow fence design: estimation of the snowfall and snow drift fluxes and mapping of the snow volumes accumulated at the snow fence after its deployment at the site. This report describes the protocols developed for documentation of snowfall, snow drift, and snow deposit mapping as well as a set of laboratory and field experiments performed to validate these new techniques and protocols. This report also describes the actual implementation of the developed protocols as applied to event-based monitoring at various locations exposed to snow drift.

A set of non-intrusive measurement techniques were innovatively assembled to document snowfall and snow drifting over roads protected by snow fences. The present research proposes the use of particle tracking velocimetry (PTV) and large-scale particle image velocimetry (LSPIV) coupled with three-dimensional (3D) photogrammetry to quantify, through direct measurements, the snowfall and snow drift fluxes. The report proposes strategies for providing adequate illumination, setting camera parameters, and processing the raw information with commercially available software to obtain accurate and robust estimations of the main variables of interest.

Snow drift measurements were demonstrated in laboratory conditions with modeled snow particles. Additionally, the present research refines previously proposed methods to determine the volume of snow retained by the fence. The approach is based on close-range 3D photogrammetry and provides a general methodology for non-intrusive remote estimation of the snow deposit volume using automated data acquisition protocols.

Publications

Report: Improving Traffic Safety through Better Snow Fences: Image-Based Methods to Measure Trapped Snow Volume and the Snow Relocation Coefficient (11.11 mb pdf) September 2017

Tech transfer summary: Improving Traffic Safety through Better Snow Fences: Image-Based Methods to Measure Trapped Snow Volume and the Snow Relocation Coefficient (777.81 kb pdf) Sep 2017

Sponsor(s)/partner(s)

Sponsor(s):

  • IIHR-Hydroscience and Engineering
  • Midwest Transportation Center
  • USDOT/OST-R

Partner(s): Department of Civil and Environmental Engineering & IIHR-Hydroscience and Engineering, UofI