SBIR/STTR Research Award

SBIR Phase I: Icy Road Forecast and Alert Product Using Road-Physics-Enhanced Weather Forecast Model and Remote Sensing Technologies

Award identifier 8c241bc602e3ed8d22b088cbdfe0a968bccdb84f120e6603656db54c59995244Awarding agency National Science Foundation

Award amount

$225,000

Program and phase

SBIR · Phase I

Award year

2020

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
SpringGem Weather Information, LLC
Proposal award date
2020-02-01
Contract end date
2021-01-31
UEI
FFFNG83J2BB8
Solicitation number
Not reported
Topic code
IT

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to reduce risks on icy winter roads and thus enhance transportation safety. Snow-covered and icy roads result in fatalities and disruption of commercial transportation. Decision-makers in government and industry need real-time observations and reliable weather forecasts to support timely decisions to reduce risks associated with icy road conditions. This SBIR project aims to develop and commercialize an innovative technology to detect, forecast and alert end users to icy road conditions. This Small Business Innovation Research (SBIR) Phase I project will integrate multi-satellite precipitation (liquid and frozen) and remote cloud sensing observations with a new physics-based road condition forecasting model to produce timely, secure, and efficient prediction of icy road conditions. Specifically, the proposed technology will use NOAA rainfall observations and NASA cloud observation services to assess surface temperature and water availability at a road surface, the two key parameters for ice formation on a road. In addition, a model incorporating a new surface energy budget and parameters to represent the physical and thermodynamic processes of road energy transportation will be developed to forecast icy road conditions up to 24 hours in advance. Furthermore, drone-mounted hyperspectral cameras using visible and near-infrared bands to detect ice on road surfaces will be developed. Collected black ice data from such cameras will be compared with the ground measurements from Road Weather Information Systems (RWIS) for validation. By combining these three new approaches, the technology is expected to reach an accuracy of approximately 85% for icy road forecasts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Agency intelligence

National Science Foundation

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