Predictive modeling of hourly probabilities for weather-related road accidents

Becker, Nico; Rust, Henning W.; Ulbrich, Uwe

doi:https://doi.org/10.5194/nhess-20-2857-2020

Articles | Volume 20, issue 10

https://doi.org/10.5194/nhess-20-2857-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-20-2857-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 10

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

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Final revised paper (published on 29 Oct 2020)
Supplement to the final revised paper
Preprint (discussion started on 09 Mar 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Interesting and useful paper looking at accident data and the variables important for modelling this', Anonymous Referee #1, 27 Mar 2020
- AC1: 'Response to comments', Nico Becker, 25 Jun 2020
RC2: 'Review of “Predictive modeling of hourly probabilities for weather-related road Accidents” by Nico Becker, Henning W. Rust, and Uwe Ulbrich', Anonymous Referee #2, 28 Mar 2020
- AC2: 'Response to comments', Nico Becker, 25 Jun 2020
RC3: 'Interesting and novel paper using weather data for short-term accident prediction, with some pending issues', Anonymous Referee #3, 14 May 2020
- AC3: 'Response to comments', Nico Becker, 25 Jun 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (further review by editor and referees) (26 Jun 2020) by Joaquim G. Pinto

AR by Nico Becker on behalf of the Authors (31 Jul 2020) Author's response Manuscript

ED: Referee Nomination & Report Request started (08 Aug 2020) by Joaquim G. Pinto

RR by Anonymous Referee #1 (10 Aug 2020)

RR by Anonymous Referee #3 (12 Aug 2020)

ED: Publish subject to technical corrections (09 Sep 2020) by Joaquim G. Pinto

AR by Nico Becker on behalf of the Authors (10 Sep 2020) Author's response Manuscript

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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.