Citation

Diependaele K, Martensen H, Lerner M, Schepers A, Bijleveld F, Commandeur JJF. Accid. Anal. Prev. 2019; 125: 336-343.

Affiliation

Stichting Wetenschappelijk Onderzoek Verkeersveiligheid, Den Haag, The Netherlands; Vrije Universiteit, Amsterdam, The Netherlands.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.aap.2018.07.022

PMID

30131101

Abstract

At the end of each year, the German Federal Highway Research Institute (BASt) publishes the road safety balance of the closing year. They describe the development of accident and casualty numbers disaggregated by road user types, age groups, type of road and the consequences of the accidents. However, at the time of publishing, these series are only available for the first eight or nine months of the year. To make the balance for the whole year, the last three or four months are forecasted. The objective of this study was to improve the accuracy of these forecasts through structural time-series models that include effects of meteorological conditions. The results show that, compared to the earlier heuristic approach, root mean squared errors are reduced by up to 55% and only two out of the 27 different data series yield a modest rise of prediction errors. With the exception of four data series, prediction accuracies also clearly improve incorporating meteorological data in the analysis. We conclude that our approach provides a valid alternative to provide input to policy makers in Germany.

Copyright © 2018 Elsevier Ltd. All rights reserved.

Language: en

Keywords

Meteorological effects; Road safety; Structural time-series model