Evaluating causes of animal-vehicle collisions through the lens of driver behavior

Animal-vehicle collisions (AVCs) are ubiquitous in developed regions of the world and pose risks to both wildlife and humans. In the United States, collisions with deer (Odocoileus spp.) cause billions of dollars in economic losses and thousands of human injuries annually. The current AVC literature has largely focused on factors unrelated to driver behavior including AVC hotspots, wildlife movement, and damages caused by AVCs. However, despite being a component in every AVC, few studies have investigated driver behavior during animal-vehicle interactions. Here, we systematically reviewed literature databases to identify factors influencing driver behavior during these interactions and to highlight apparent gaps in the literature. We found that vehicle speed, road attributes, environmental conditions, and vehicle types show inconsistent associations with AVCs and the mechanisms by which they influence driver behavior is not well understood. Many studies focused on mitigation methods to influence driver behavior, including various warning signs; however, the effectiveness of these systems varies considerably. Other topics including wildlife attributes, roadway illumination, and inherent driver attributes directly influence driver behavior, but are understudied. Most studies relied on seemingly logical explanations for results or associations between variables to identify these influences, but few studies directly tested how specific variables influenced driver behavior and detection ability of wildlife. Given that driver behavior influences every potential AVC, future research should directly investigate the behavioral and perceptual mechanisms behind driver detection of wildlife and other factors influencing overall driver behavior during wildlife-vehicle interactions.