Modeling animal-vehicle collisions considering animal-vehicle interactions

Yunteng Lao, Guohui Zhang, Yao Jan Wu, Yinhai Wang

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

Animal-Vehicle Collisions (AVCs) have been a major safety problem in the United States over the past decades. Counter measures against AVCs are urgently needed for traffic safety and wildlife conservation. To better understand the AVCs, a variety of data analysis and statistical modeling techniques have been developed. However, these existing models seldom take human factors and animal attributes into account. This paper presents a new probability model which explicitly formulates the interactions between animals and drivers to better capture the relationship among drivers' and animals' attributes, roadway and environmental factors, and AVCs. Findings of this study show that speed limit, rural versus urban, and presence of white-tailed deer habitat have an increasing effect on AVC risk, whereas male animals, high truck percentage, and large number of lanes put a decreasing effect on AVC probability.

Original languageEnglish (US)
Pages (from-to)1991-1998
Number of pages8
JournalAccident Analysis and Prevention
Volume43
Issue number6
DOIs
StatePublished - Nov 1 2011
Externally publishedYes

Keywords

  • Accident modeling
  • Animal-vehicle collision
  • Carcass removal
  • Negative binomial (NB) regression
  • Roadway Safety
  • Vehicle-animal interaction-based probability model

ASJC Scopus subject areas

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

Fingerprint Dive into the research topics of 'Modeling animal-vehicle collisions considering animal-vehicle interactions'. Together they form a unique fingerprint.

  • Cite this