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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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A set of models is developed to forecast hourly probabilities of weather-related road accidents in Germany at the spatial scale of administrative districts. Model verification shows that using precipitation and temperature data leads to the best accident forecasts. Based on weather forecast data we show that skilful predictions of accident probabilities of up to 21 h ahead are possible. The models can be used to issue impact-based warnings, which are relevant for road users and authorities.
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NHESS | Articles | Volume 20, issue 10
Nat. Hazards Earth Syst. Sci., 20, 2857–2871, 2020
https://doi.org/10.5194/nhess-20-2857-2020
Nat. Hazards Earth Syst. Sci., 20, 2857–2871, 2020
https://doi.org/10.5194/nhess-20-2857-2020

Research article 29 Oct 2020

Research article | 29 Oct 2020

Predictive modeling of hourly probabilities for weather-related road accidents

Nico Becker et al.

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Cited articles

Ahmed, M. M., Abdel-Aty, M., and Yu, R.: Assessment of interaction of crash occurrence, mountainous freeway geometry, real-time weather, and traffic data, Transp. Res. Record, 2280, 51–59, https://doi.org/10.3141/2280-06, 2012. a
Akaike, H.: A new look at the statistical model identification, IEEE Trans. Automat. Contr., 19, 716–723, https://doi.org/10.1007/978-1-4612-1694-0_16, 1974. a
Bartels, H., Weigl, E., Reich, T., Lang, P., Wagner, A., Kohler, O., and Gerlach, N.: Projekt RADOLAN – Routineverfahren zur Online-Aneichung der Radarniederschlagsdaten mit Hilfe von automatischen Bodenniederschlagsstationen (Ombrometer), Deutscher Wetterdienst, Hydrometeorologie, available at: https://www.dwd.de/DE/leistungen/radolan/radolan.html (last access: 28 October 2020), 2004. a, b
BASt: Verkehrs- und Unfalldaten – Kurzzusammenstellung der Entwicklung in Deutschland, Tech. rep., Bundesanstalt für Straßenwesen, Bergisch Gladbach, Germany, 2017. a
Benedetti, R.: Scoring rules for forecast verification, Mon. Weather Rev., 138, 203–211, https://doi.org/10.1175/2009MWR2945.1, 2010. a
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Short summary
A set of models is developed to forecast hourly probabilities of weather-related road accidents in Germany at the spatial scale of administrative districts. Model verification shows that using precipitation and temperature data leads to the best accident forecasts. Based on weather forecast data we show that skilful predictions of accident probabilities of up to 21 h ahead are possible. The models can be used to issue impact-based warnings, which are relevant for road users and authorities.
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Final-revised paper
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