Modeling animal-vehicle collisions using diagonal inflated bivariate Poisson regression

Yunteng Lao, Yao Jan Wu, Jonathan Corey, Yinhai Wang

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Two types of animal-vehicle collision (AVC) data are commonly adopted for AVC-related risk analysis research: reported AVC data and carcass removal data. One issue with these two data sets is that they were found to have significant discrepancies by previous studies. In order to model these two types of data together and provide a better understanding of highway AVCs, this study adopts a diagonal inflated bivariate Poisson regression method, an inflated version of bivariate Poisson regression model, to fit the reported AVC and carcass removal data sets collected in Washington State during 2002-2006. The diagonal inflated bivariate Poisson model not only can model paired data with correlation, but also handle under- or over-dispersed data sets as well. Compared with three other types of models, double Poisson, bivariate Poisson, and zero-inflated double Poisson, the diagonal inflated bivariate Poisson model demonstrates its capability of fitting two data sets with remarkable overlapping portions resulting from the same stochastic process. Therefore, the diagonal inflated bivariate Poisson model provides researchers a new approach to investigating AVCs from a different perspective involving the three distribution parameters (λ1, λ2 and λ3). The modeling results show the impacts of traffic elements, geometric design and geographic characteristics on the occurrences of both reported AVC and carcass removal data. It is found that the increase of some associated factors, such as speed limit, annual average daily traffic, and shoulder width, will increase the numbers of reported AVCs and carcass removals. Conversely, the presence of some geometric factors, such as rolling and mountainous terrain, will decrease the number of reported AVCs.

Original languageEnglish (US)
Pages (from-to)220-227
Number of pages8
JournalAccident Analysis and Prevention
Volume43
Issue number1
DOIs
StatePublished - Jan 1 2011
Externally publishedYes

Keywords

  • Accident modeling
  • Animal-vehicle collision
  • Bivariate Poisson model
  • Carcass removal and roadway safety
  • Diagonal inflated bivariate Poisson model
  • Double Poisson model

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health

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