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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8285

Title: A model for identifying and ranking dangerous accident locations: a case study in Flanders (vol 60, pg 457, 2006)
Authors: BRIJS, Tom
WETS, Geert
KARLIS, Dimitris
Issue Date: 2007
Citation: STATISTICA NEERLANDICA, 61(2). p. 271-271
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/1942/8285
DOI: 10.1111/j.1467-9574.2006.00341.x
ISI #: 000245992100006
ISSN: 0039-0402
Category: M
Type: Journal Contribution
Appears in Collections: Research publications

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