The RIM offers both diagnostic and prognostic assessment of road-icing risk independent of road-surface observations. The model categorizes icing risk using a hierarchical system that utilizes: (a) observational output from the Oklahoma Mesonet and Automated Surface Observation Station (ASOS) network for diagnostic road icing risk assessment, and (b) model output from the National Weather Service (NWS) monitored National Digital Forecast Database (NDFD) for prognostic assessment. The RWIS was developed using novel, cost-effective methods, and is comprised of stations built from off-the-shelf piezoelectric sensors, microprocessors, and wireless modules. A stochastic method is used to determine road icing risk, which may be readily assimilated into the diagnostic portions of RIM. Using a combination of the output from the RWIS and RIM, a customized GIS visualization software offers road-scale road icing information. Supplementary information regarding traffic flow, population, and topography is available for rapid in-situ warning of road icing. The combination of an observationally parameterized road icing model, an RWIS, and a GIS visualization package captures the wide range of road icing risk, while offering computational efficiency and economical deployment.