It is more likely that drivers become accustomed to deer crossing signs than cow signs. The differences between AVCs that occurred within versus outside of sign recognition distance were not statistically significant regarding crash severity, time of crash, weather condition, driver age, vehicle speed, and type of animal. State routes with a higher average number of signs experienced a lower number of AVCs per mile. highways, wherein only 30% of animal crossing signs were installed. Almost 58% of animal-related crashes took place on the Interstate and U.S. Results: Only 2% of AVCs occurred within the recognition distance of animal crossing signs. Kernel density estimation (KDE) technique was applied to identify potential crash hotspots. An algorithm was developed to process the data and identify AVCs that occurred within sign recognition distance. ArcGIS was employed to link these two data sets and extract animal-related crashes and signs. The crash data were obtained from the UDOT risk management database. Method: A mobile-based data collection effort was deployed to measure signs under the Utah Department of Transportation's (UDOT) jurisdiction. However, the cost effectiveness of the majority of AVC mitigation measures is a significant issue. Introduction: Animal–vehicle collisions (AVCs) can result in serious injury and death to drivers, animals' death, and significant economic costs.
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