01475853

Component

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.

This paper was sponsored by TRB committee ABJ80 Statistical Methods.

01470560

13-1061

English

21p

2013

Transportation Research Board 92nd Annual Meeting

Digital/other

Figures; References; Tables

Crash data; Crash rates; High risk locations; Multivariate analysis; Risk analysis; Spatial analysis

Costa Rica

Highways; Safety and Human Factors; I80: Accident Studies

Transportation Research Board Annual Meeting 2013 Paper #13-1061

TRIS, TRB, ATRI

Feb 5 2013 12:19PM