A Bayesian model for ranking hazardous road sites.

Author(s)
Brijs, T. Karlis, D. vandenBossche, F. & Wets, G.
Year
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. (Author/publisher)

Publication

Library number
20072375 ST [electronic version only]
Source

Journal of the Royal Statistical Society Series A - Statistics in Society, Vol. 170 (2007), Part 4 (October), p. 1001-1017, ref.

Our collection

This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.