Articles | Volume 20, issue 10
https://doi.org/10.5194/nhess-20-2857-2020
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, Henning W. Rust, and Uwe Ulbrich

Viewed

Total article views: 2,739 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,875 788 76 2,739 68 71 74
  • HTML: 1,875
  • PDF: 788
  • XML: 76
  • Total: 2,739
  • Supplement: 68
  • BibTeX: 71
  • EndNote: 74
Views and downloads (calculated since 09 Mar 2020)
Cumulative views and downloads (calculated since 09 Mar 2020)

Viewed (geographical distribution)

Total article views: 2,739 (including HTML, PDF, and XML) Thereof 2,533 with geography defined and 206 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
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.
Altmetrics
Final-revised paper
Preprint