Studying the effect on weather conditions on daily crash counts.

Author(s)
Brijs, T. Karlis, D. & Wets, G.
Year
Abstract

In previous research, significant effects of weather conditions on car crashes have been found. However, most studies use monthly or yearly data and only few studies are available analyzing the impact of weather conditions on daily car crash counts. Furthermore, the studies that are available on a daily level do not model the data in a time-series context, hereby ignoring the temporal serial correlation that may be present in the data. In this paper, we introduce an Integer Autoregressive model for modelling count data with time interdependencies. The model is applied to daily car crash data and meteorological data from the Netherlands aiming at examining the risk impact of weather conditions on the observed counts. The results show that several assumptions related to the effect of weather conditions on crash counts are found to be significant in the data and that an appropriate statistical model should be used to account for the existing autocorrelation in the data. (A) For the covering abstract of the conference see E216632.

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Publication

Library number
C 43230 (In: C 43218 CD-ROM) /80 / ITRD E216644
Source

In: Proceedings the 14th International Conference on Road Safety on Four Continents, Bangkok, Thailand 14-16 November 2007, 12 p., 29 ref.

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