Citation

Aguero-Valverde J. Accid. Anal. Prev. 2013; 59: 365-373.

Affiliation

Programa de Investigación en Desarrollo Urbano Sostenible, Universidad de Costa Rica, Barrio Los Profesores, Calle B, No. 11, Mercedes, San Pedro, San José 11503, Costa Rica. Electronic address: jonathan.aguero@ucr.ac.cr.

Copyright

(Copyright © 2013, Elsevier Publishing)

DOI

10.1016/j.aap.2013.06.014

PMID

23872657

Abstract

Recently, areal models of crash frequency have being used in the analysis of various area-wide factors affecting road crashes. On the other hand, disease mapping methods are commonly used in epidemiology to assess the relative risk of the population at different spatial units. A natural next step is to combine these two approaches to estimate the excess crash frequency at area level as a measure of absolute crash risk. Furthermore, multivariate spatial models of crash severity are explored in order to account for both frequency and severity of crashes and control for the spatial correlation frequently found in crash data. This paper aims to extent the concept of safety performance functions to be used in areal models of crash frequency. A multivariate spatial model is used for that purpose and compared to its univariate counterpart. Full Bayes hierarchical approach is used to estimate the models of crash frequency at canton level for Costa Rica. An intrinsic multivariate conditional autoregressive model is used for modeling spatial random effects. The results show that the multivariate spatial model performs better than its univariate counterpart in terms of the penalized goodness-of-fit measure Deviance Information Criteria. Additionally, the effects of the spatial smoothing due to the multivariate spatial random effects are evident in the estimation of excess equivalent property damage only crashes.

Language: en