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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/1497

Title: A model for identifying and ranking dangerous accident locations: a case study in Flanders
Authors: BRIJS, Tom
WETS, Geert
KARLIS, Dimitris
Issue Date: 2006
Publisher: Blackwell
Citation: STATISTICA NEERLANDICA, 60(4). p. 457-476
Abstract: These days, road safety has become a major concern in most modern societies. In this respect, the determination of road locations that are more dangerous than others (black spots or also called sites with promise) can help in better scheduling road safety policies. The present paper proposes a multivariate model to identify and rank sites according to their total expected cost to the society. Bayesian estimation of the model via a Markov Chain Monte Carlo approach is discussed in this paper. To illustrate the proposed model, accident data from 23,184 accident locations in Flanders (Belgium) are used and a cost function proposed by the European Transport Safety Council is adopted to illustrate the model. It is shown in the paper that the model produces insightful results that can help policy makers in prioritizing road infrastructure investments.
URI: http://hdl.handle.net/1942/1497
DOI: 10.1111/j.1467-9574.2006.00341.x
ISI #: 000241197000004
ISSN: 0039-0402
Category: A1
Type: Journal Contribution
Validation: ecoom, 2007
Appears in Collections: Research publications

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