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Journal Article

Citation

Wilkins DC, Kockelman KM, Jiang N. Accid. Anal. Prev. 2019; 131: 157-170.

Affiliation

Research Associate, Center for Transportation Research, The University of Texas at Austin, Austin, TX 78759, United States. Electronic address: jiang@utexas.edu.

Copyright

(Copyright © 2019, Elsevier Publishing)

DOI

10.1016/j.aap.2019.05.030

PMID

31277019

Abstract

Animal-vehicle collisions (AVCs) are a growing problem in the United States, resulting in countless loss of animal life and considerable human injury and death every year, especially to motorcyclists. Due to underreporting, collision data generally provide a very low (highly biased) estimate of actual AVC counts and often lack key details, such as the species of animals involved. However, AVC reports cover entire states and nations, and can illuminate differences in wild versus domestic animal-vehicle collisions through statistical and spatial analysis. 51,522 animal-related crashes were reported to Texas police from 2010 through 2016, at a total cost over $1.3 billion annually to Texas motorists - not including the value of lost animal lives. AVC reports jump twice a day: between 5 and 8 AM and between 5 and 10 PM. Motorists are also significantly more likely to collide with a wild animal during the months of October, November, and December. Wildlife-vehicle collisions (WVC) are 64% of total reports, events involving domestic animals (like dogs and cattle) are 31%, and the remaining 5% of reports are unspecified. Most AVCs in the state occur at night in unlit locations, usually on rural roads with very low traffic volumes. Using ordinary least-squares (OLS) regression analysis across Texas' n = 254 counties, this work finds that less densely populated counties, marked as rural, and those with fewer vehicle-miles traveled (VMT) per capita but more lane-miles per capita, tend to experience the greatest number of AVCs per VMT, after controlling for county average rainfall, share of VMT onsystem roadways, job densities, and vehicle ownership (vehicles per capita). Intervention options for the mitigation of animal-vehicle collisions are numerous and diverse. For wildlife collisions specifically, this work finds that large crossing structures (underpasses and overpasses) at the highway link level return benefit-to-cost ratios near 3.0, while their lower-cost counterparts (wildlife fencing and animal detection systems) deliver ratios up to 30.

Copyright © 2019. Published by Elsevier Ltd.


Language: en

Keywords

Animal detection systems; Animal-vehicle collisions; Benefit-cost analysis; Crashes; Fencing; Overpasses; Texas; Underpasses; Wildlife

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