Machine Learning Approaches to Estimate Road Surface Temperature Variation along Road Section in Real-Time for Winter Operation

Black, A.W., Mote, T.L.: Effects of winter precipitation on automobile collisions, injuries, and fatalities in the United States. J. Transp. Geogr. 48, 165–175 (2015). https://doi.org/10.1016/j.jtrangeo.2015.09.007

Feng, F., Fu, L.: Winter road surface condition forecasting. J. Infrastruct. Syst. 21(3), 1–12 (2015). https://doi.org/10.1061/(ASCE)IS.1943-555X.0000241

Nordin, L., Riehm, M., Gustavsson, T., Bőrgren, J.: Road surface wetness variations: measurements and effects for winter road maintenance. J. Transp. Eng. 139(8), 787–796 (2013). https://doi.org/10.1061/(ASCE)TE.1943-5436.0000546

Michael Fitch, G., Smith, J.A., Clarens, A.F.: Environmental life-cycle assessment of winter maintenance treatments for roadways. J. Transp. Eng. 139(2), 138–146 (2013). https://doi.org/10.1061/(ASCE)TE.1943-5436.0000453

Federal Highway Administration (FHWA). How do weather events impact roads?, Available at: http://ops.fhwa.dot.gov/Weather/q1_roadimpact.htm (2005). Accessed 13 Mar 2018

Pisano, P. (2010). Seasons of achievement: accomplishments of the road weather management program, Report No. FHWA-JPO-10-004

Sass, B.H.: A numerical forecasting system for the prediction of slippery roads. J. Appl. Meteorol. 36(6), 801–817 (1997). https://doi.org/10.1175/1520-0450(1997)036<0801:ANFSFT>2.0.CO;2

Shao, J., Lister, P.J.: An automated nowcasting model of road surface temperature and state for winter road maintenance. J. Appl. Meteorol. 35(8), 1352–1361 (1996). https://doi.org/10.1175/1520-0450(1996)035<1352:AANMOR>2.0.CO;2

Sass, B.H.: A numerical model for prediction of road temperature and ice. J. Appl. Meteorol. 31(12), 499–1506 (1993). https://doi.org/10.1175/1520-0450(1992)031<1499:ANMFPO>2.0.CO;2

Voldborg, H. : On the prediction of road conditions by a combined road layer-atmospheric model in winter. Transportation Research Record. (1387), 231–235 (1993)

Takahashi, N., Tokunaga, R.A., Asano, M., Ishikawa, N.: Toward strategic snow and ice control on roads: developing method for surface-icing forecast by applying heat balance model. Proceedings of the Transportation Research Board. (2006) 85th Annual Meeting, Washington, D.C., USA

Takahashi, N., Tokunaga, R.A., Asano, M., Ishikawa, N.: Road surface temperature prediction model taking into account effects of the surrounding environment. Proceedings of the Transportation Research Board. (2008) 85th Annual Meeting, Washington, D.C., USA

Feng, T., Feng, S.: A numerical model for predicting road surface temperature in the highway. Procedia Engineering. 37, 137–142 (2012). https://doi.org/10.1016/j.proeng.2012.04.216

Kangas, M., Heikinheimo, M., Hippi, M.: RoadSurf: a modelling system for predicting road weather and road surface conditions. Meteorol. Appl. 22(3), 533–544 (2015). https://doi.org/10.1002/met.1486

Karsisto, V., Nurmi, P., Kangas, M., Hippi, M., Fortelius, C., Niemelä, S., Järvinen, H.: Improving road weather model forecasts by adjusting the radiation input. Meteorol. Appl. 23(3), 503–513 (2016). https://doi.org/10.1002/met.1574

Meng, C.: A numerical forecast model for road meteorology. Meteorog. Atmos. Phys. 130(4), 485–498 (2017). https://doi.org/10.1007/s00703-017-0527-8

Karsisto, V., Nurmi, P.: Using car observations in road weather forecasting. In: Proceedings of the 18th International Road Weather Conference (SIRWEC), Fort Collins, Colorado, USA (2016)

Habrovsky, R., Tarjáni, V.: Kalman filter preprocessing within ´METRoSTAT project and application of the new method in the roadcast system. In: Proceedings of the 17th International Road Weather Conference (SIRWEC), La Massana, vol. 30, Andorra (2014)

Homleid, M.: Diurnal corrections of short-term surface temperature forecasts using the Kalman filter. Weather Forecast. 10(4), 689–707 (1995). https://doi.org/10.1175/1520-0434(1995)010<0689:DCOSTS>2.0.CO;2

Shao, J. Improving nowcasts of road surface temperature by a backpropagation neural network. Weather Forecast., 13, 164–171 (1997)

Shao, J., Lister, P.J., Hart, G.D., Pearson, H.B.: Thermal mapping: reliability and repeatability. J. Appl. Meteorol. 3(4), 325–330 (1996). https://doi.org/10.1002/met.5060030405

Numata, M., Okamoto, J., Tashiro, T., Ito, T.: A basic study of short term forecasting methods of snowfall and road surface temperature using intelligent visibility meter. In: Proceedings of the 11th International Road Weather Conference, Sapporo, Japan (2002)

Chapman, L., Thornes, J.E.: A geomatics-based road surface temperature prediction model. Sci. Total Environ. 360(1), 68–80 (2006). https://doi.org/10.1016/j.scitotenv.2005.08.025

Xu, B., Dan, H.C., Li, L.: Temperature prediction model of asphalt pavement in cold regions based on an improved BP neural network. Appl. Therm. Eng. 120(25), 568–580 (2017). https://doi.org/10.1016/j.applthermaleng.2017.04.024

Marchetti, M., Chapman, L., Khalifa, A., and Buès, M. (2014). New role of thermal mapping in winter maintenance with principal components analysis. Adv. Meteorol., Vol. 2014, Article ID 254795, pp. 1–11, https://doi.org/10.1155/2014/254795

Marchetti, M., Khalifa, A., and Bues, M. (2015). Methodology to forecast road surface temperature with principal components analysis and partial least-square regression: application to an urban configuration. Advances in Meteorology, Vol. 2015, Article ID 562621, pp. 1–10, DOI: 10.1155/2015/562621

Gustavsson, T.: Variation in road surface temperature due to topography and wind. Theor. Appl. Climatol. 41(4), 227–236 (1990)

Chapman, L., Thornes, J.E., Bradley, A.V.: Modelling of road surface temperature from a geographical parameter database. Part 1: statistical. Meteorol. Appl. 8(4), 409–419 (2001). https://doi.org/10.1017/S1350482701004030

Thornes, J.E., Shao, J.: A comparison of UK road ice prediction models. Meteorol. Mag. 120(1424), 51–57 (1991)

Wu, Y., Liu, Y.: Robust truncated hinge loss support vector machines. J. Am. Stat. Assoc. 102(479), 974–983 (2012). https://doi.org/10.1198/016214507000000617