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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/3995

Title: A Bayesian model for ranking hazardous road sites
Authors: BRIJS, Tom
KARLIS, Dimitris
VAN DEN BOSSCHE, Filip
WETS, Geert
Issue Date: 2007
Publisher: BLACKWELL PUBLISHING
Citation: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY, 170. p. 1001-1017
Abstract: Road safety has recently become a major concern in most modern societies. The identification of sites that are more dangerous than others (black spots) can help in better scheduling road safety policies. This paper proposes a methodology for ranking sites according to their level of hazard. The model is innovative in at least two respects. Firstly, it makes use of all relevant information per accident location, including the total number of accidents and the number of fatalities, as well as the number of slight and serious injuries. Secondly, the model includes the use of a cost function to rank the sites with respect to their total expected cost to society. Bayesian estimation for the model via a Markov chain Monte Carlo approach is proposed. Accident data from 519 intersections in Leuven (Belgium) are used to illustrate the methodology proposed. Furthermore, different cost functions are used to show the effect of the proposed method on the use of different costs per type of injury.
Notes: Hasselt Univ, Transportat Res Inst, B-3590 Diepenbeek, Belgium. Athens Univ Econ & Business, Athens, Greece.BRIJS, T, Hasselt Univ, Transportat Res Inst, Wetenschapspk,Gebouw 5, B-3590 Diepenbeek, Belgium.tom.brijs@uhasselt.be
URI: http://hdl.handle.net/1942/3995
DOI: 10.1111/j.1467-985X.2007.00486.x
ISI #: 000249827500009
ISSN: 0964-1998
Category: A1
Type: Journal Contribution
Validation: ecoom, 2008
Appears in Collections: Research publications

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