title: Modeling animal-vehicle collisions considering animal-vehicle interactions.
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.
authors.affiliation: Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA. Electronic address: laoy@u.washington.edu.
authors.forename: Yunteng
authors.initials: Y
authors.lastname: Lao
authors.affiliation: Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX 78705, USA. Electronic address: guohui@mail.utexas.edu.
authors.forename: Guohui
authors.initials: G
authors.lastname: Zhang
authors.affiliation: Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA. Electronic address: yaojan@u.washington.edu.
authors.forename: Yao-Jan
authors.initials: YJ
authors.lastname: Wu
authors.affiliation: Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195, USA. Electronic address: yinhai@u.washington.edu.
authors.forename: Yinhai
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data*; D000818:Animals; D003670:Deer; D006801:Humans; D015233:Models, Statistical; D018986:Motor Vehicles / Q000706:statistics & numerical data; D011930:Reaction Time; D012044:Regression Analysis; D012307:Risk Factors; D012424:Rural Population / Q000706:statistics & numerical data; D014505:Urban Population / Q000706:statistics & numerical data