Affiliation:
1. Department of Civil and Environmental Engineering, Kunsan National University, Gunsan City, Rep. of Korea
2. Department of Computer Information Engineering, Kunsan National University, Gunsan City, Rep. of Korea
Abstract
Black ice is a thin coating of ice on the road surface, which strongly reduces friction at the tire-road surface, resulting in dangerous driving when it happens. An appropriate diagnostic of black ice could prevent traffic accidents as well as provide timely notice to drivers. Therefore, this study aims at developing a black ice prediction model to diagnose the probability of black ice formation. Several combinations that can form road ice have been considered, including freezing rain, hoar frost, freezing of wet roads. In addition, black ice risky index (BRI) has been computed to reflect the probability of black ice formation. To acquire a fast prediction and high accuracy, the existing Geographical Information System (GIS) database and meteorological data have been utilized. GIS database includes road geometry and location of automatic weather stations, while the meteoritical data consists of air temperature, wind speed, humidity, cloud cover. The model has been developed based on the Python programming language. A 5-km road condition was observed from 1 December to 31 December 2021 to determine the model accuracy. Based on the results from the prediction model, black ice formation has been verified when the BRI is higher than 0.8. The model may be useful to develop black ice diagnostic program.
Funder
Korea Agency for Infrastructure Technology Advancement
Publisher
Riga Technical University
Subject
Building and Construction,Civil and Structural Engineering
Reference21 articles.
1. Barszcz, A., Milbrandt, J. A., & Thériault, J. M. (2018). Improving the explicit prediction of freezing rain in a kilometer-scale numerical weather prediction model. Weather and Forecasting, 33(3), 767–782. https://doi.org/10.1175/WAF-D-17-0136.1
2. Gocheva, A. (1990). Statistical distribution of air temperature, relative humidity and wind velocity during rime-icing for the non-mountain part of the territory of Bulgaria. Proceedings of 5th International Youth School on Meteorology and Hydrology, 4, 84–89.
3. Gode, K., & Paeglitis, A. (2014). Concrete bridge deterioration caused by de-icing salts in high traffic volume road environment in Latvia. The Baltic Journal of Road and Bridge Engineering, 9(3). https://doi.org/10.3846/bjrbe.2014.25
4. Gustavsson, T. & Bogren, J. (1990). Road slipperiness during warm air advection. Meteorological Magazine, 119, 267–270.
5. Hong, S.-B., Lee, B.-W., Kim, C.-H., & Yun, H.-S. (2021). System dynamics modeling for estimating the locations of road Icing using GIS. Applied Sciences, 11(18), Article 8537. https://doi.org/10.3390/app11188537
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