Reliability and Meta-Analyses of the Effectiveness of Animal Detection Systems in Reducing Vehicle Speed and Collisions with Large Mammals
Started: October, 2015 End Date: December, 2017 Project ID #4W5839 Status: Ongoing
This purpose of this project is to enhance available research on animal detection systems and expand technology transfer of the findings.
In order to reduce the number of animal-vehicle collisions, animal detection systems need to detect animals reliably, and influence driver behavior so that drivers avoid collisions. Widespread implementation of animal detection systems in hindered by numerous factors, including lack of well-designed studies that evaluate system reliability and effectiveness, scarcity of peer-reviewed publications, absence of standards for system reliability and effectiveness, and absence of clear overall data on system effectiveness. This project will include the following activities to enhance available research on animal detection systems:
- Conduct extensive data collection on the reliability and effectiveness of an animal detection system in Boundary County, Idaho, including under harsh conditions for electronic equipment and relatively dangerous driving conditions (low temperatures, snow, ice)
- Submit a paper on the reliability of animal detection systems, the effect of environmental conditions on system reliability and suggested minimum norms to a peer-reviewed journal
- Conduct meta-analysis to investigate the overall effectiveness of animal detection systems in reducing vehicle speed and collisions with large mammals.
- Submit a paper on the meta-analyses to a peer-reviewed journal.
- Present results to an international conference.
Marcel Huijser - PI
Jenny Liu - Main External Contact
Sponsors & Partners
- University of Alaska - Fairbanks Sponsor
Part of: Road Ecology, Technology and Technology Transfer, UAF-CESTiCC
Project Tagged In: Animal detection systems, wildlife vehicle collisions« Back to Focus Areas