Canadian wildlife-vehicle collisions: An examination of knowledge and behavior for collision prevention

J Safety Res. 2019 Feb;68:181-186. doi: 10.1016/j.jsr.2018.12.003. Epub 2018 Dec 14.

Abstract

Objectives: This study examines drivers' responses to wildlife on Canadian roads. The objective of this paper is to demonstrate that knowledge of what to do when encountering wildlife on the road does not always translate into the appropriate behavior to avoid a collision.

Methods: Data from the Traffic Injury Research Foundation's (TIRF) 2016 Road Safety Monitor (RSM) and data from TIRF's National Fatality Database from 2000 to 2014 were analyzed to test hypotheses based on the theory of planned behavior. Logistic regression and piecewise linear regression were used.

Results: Analyses of the data showed that the prevalence of fatal WVCs has remained relatively consistent, and that the majority of persons killed in WVCs died in crashes that involved large mammals. The majority of fatalities occurred in the summer (182 or 38.4%) and fall (163 or 34.4%). The RSM data revealed that 60.9% [50.5, 70.4] of respondents who previously hit an animal indicated that drivers should slow down and steer straight when confronted with wildlife, while 47.3% [37.1, 57.6] of respondents indicated this was the action they took when they hit wildlife. Comparatively, 59.5% [56.6, 62.4] of respondent who have not hit an animal indicated this was an appropriate response. Additionally, 33.2% [24, 44] of respondents who previously hit an animal indicated that drivers should swerve to avoid a collision with wildlife, while 37.5% [28.2, 47.8] of respondents indicated this was the action they took when they hit wildlife.

Conclusions: Many drivers are unaware of what the safest method of WVC prevention is. Further, while a subgroup of drivers may have the knowledge and intention to slow down and steer straight even if the animal is directly in the path, i.e., the safest possible behavior, they are not necessarily adopting this behavior. Practical applications: Recommendations are formulated to address this discrepancy, as well as practical applications.

Keywords: Collision prevention; Theory of planned behavior; Trends; Wildlife; Wildlife-vehicle collisions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic* / prevention & control
  • Accidents, Traffic* / statistics & numerical data
  • Adult
  • Aged
  • Animals
  • Animals, Wild*
  • Canada
  • Databases, Factual
  • Female
  • Health Knowledge, Attitudes, Practice*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Models, Theoretical
  • Prevalence
  • Records
  • Safety
  • Seasons