DOI QR코드

DOI QR Code

A Study on Prediction of Road Freezing in Jeju

제주지역 도로결빙 예측에 관한 연구

  • Received : 2018.03.28
  • Accepted : 2018.06.07
  • Published : 2018.07.31

Abstract

Road freezing caused by snowfall during wintertime causes traffic congestion and many accidents. To prevent such problems, we developed, in this study, a system to predict road freezing based on weather forecast data and the freezing generation modules. The weather forecast data were obtained from a high-resolution model with 1 km resolution for Jeju Island from 00:00 KST on December 1, 2017, to 23:00 KST on February 28, 2018. The results of the weather forecast data show that index of agreement (IOA) temperature was higher than 0.85 at all points, and that for wind speed was higher than 0.7 except in Seogwipo city. In order to evaluate the results of the freezing predictions, we used model evaluation metrics obtained from a confusion matrix. These metrics revealed that, the Imacho module showed good performance in precision and accuracy and that the Karlsson module showed good performance in specificity and FP rate. In particular, Cohen's kappa value was shown to be excellent for both modules, demonstrating that the algorithm is reliable. The superiority of both the modules shows that the new system can prevent traffic problems related to road freezing in the Jeju area during wintertime.

Acknowledgement

Grant : 운전자 환경 반응형 CEV(Connected Electricity Vehicle) 서비스 개발

Supported by : 산업통상자원부

References

  1. Choi, B. G., Kim, J. S., 2005, Extraction of road surface freezing section using GIS, Journal of The Korea Society For Geospatial Information Science, 4(34), 19-25.
  2. Imacho, N., Nakamura, T., Hashiba, K., 2002, Road icing detection and forecasting system using optical fiber sensors for use in road management in winter, Hitachi Cable Review, 21, 29-34.
  3. Karlsson, M., 2001, Prediction of hoar-frost by use of a road weather information system, Meteorol. Appl., 8(1), 95-105. https://doi.org/10.1017/S1350482701001086
  4. Kim, J. W., Jung, Y. W., Nam, J. W., 2013, Study on the development of road icing forecast and snow detection system using state evaluation algorithm of multi sensoring method, KSMI, 17(5), 113-121.
  5. Kim, J. W., Kim, H. G., 2010, Introduction of prevention and prediction techniques of road surface freezing, Magazine of The Korean Society of Hazard Mitigation, 10(4), 35-39.
  6. Kim, S. Y., Jang, Y. S., Kim, S. K., Min, D. C., Na, H. H., Choi, J. S., 2015, A Study on the effects of factors of traffic accidents caused by frozen urban road surfaces in the winter, Int. J. Highw. Eng., 17(2), 79-87. https://doi.org/10.7855/IJHE.2015.17.2.079
  7. Koroad, 2018, https://www.koroad.or.kr.
  8. Lee, S. J., 2017, A Study on factors that influence traffic accident severity in road surface freezing. KOSOS, 32(6), 150-156.
  9. Lee, Y. M., Bae, J. H., Park, J. K., 2016, A Study on fog forecasting method through data mining techniques in Jeju, JESI, 25(4), 603-613.
  10. Seo, M. G., 2014, Data processing using the R & industry analysis, Gilbut Inc., 447-450.
  11. Sin, G. H., Song, Y. J., You, Y. G., 2011, Bridge road surface frost prediction and monitoring system, Jour. of KoCon.a., 11(11), 42-48.
  12. Sonntag, D., 1990, Important new values of the physical constants of 1986, vapour pressure formulations based on the ITS-90 and psychrometer formulae, Z. Meteorol., 70(5), 340-344.
  13. Yaser, S. A., Malik, M. I., Lin, H. T., 2012, Learning from data, AML Book, 32-39.