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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8234

Title: Studying the effect of weather conditions on daily crash counts using a discrete time-series model
Authors: BRIJS, Tom
KARLIS, Dimitris
WETS, Geert
Issue Date: 2008
Citation: ACCIDENT ANALYSIS AND PREVENTION, 40(3). p. 1180-1190
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 explicitly 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, metereological data and traffic exposure 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 if serial temporal correlation is not accounted for in the model, this may produce biased results.
URI: http://hdl.handle.net/1942/8234
DOI: 10.1016/j.aap.2008.01.001
ISI #: 000256782000038
ISSN: 0001-4575
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

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