TY - JOUR
T1 - Modeling animal-vehicle collisions considering animal-vehicle interactions
AU - Lao, Yunteng
AU - Zhang, Guohui
AU - Wu, Yao Jan
AU - Wang, Yinhai
N1 - Funding Information:
The authors are grateful for the financial support to this project from the Washington State Department of Transportation (WSDOT) and Transportation Northwest (TRANSNow) . The authors wish to express sincere appreciation to WSDOT's Environmental Services Office and Research Office personnel, specifically Kelly McAllister and Rhonda Brooks, for their help on the data collection. The authors also want to acknowledge Highway Safety Information System (HSIS) staff member Yusuf Mohamedshah for his help with data collection. Special thanks also go to Barrett Welford Taylor at the University of Washington for his editing work, and Heather Turner from University of Warwick for her suggestions on model calculation.
PY - 2011/11
Y1 - 2011/11
N2 - 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.
AB - 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.
KW - Accident modeling
KW - Animal-vehicle collision
KW - Carcass removal
KW - Negative binomial (NB) regression
KW - Roadway Safety
KW - Vehicle-animal interaction-based probability model
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U2 - 10.1016/j.aap.2011.05.017
DO - 10.1016/j.aap.2011.05.017
M3 - Article
C2 - 21819827
AN - SCOPUS:79961166284
SN - 0001-4575
VL - 43
SP - 1991
EP - 1998
JO - Accident Analysis and Prevention
JF - Accident Analysis and Prevention
IS - 6
ER -