Evaluation of a Buried Sensing Cable for Roadside Animal Detection

Animal-vehicle collisions (AVC) are a concern for departments of transportation as they translate into hundreds of human fatalities and billions of dollars in property damage each year. To reduce AVCs in the state, the Virginia Department of Transportation (VDOT) in collaboration with the Virginia Tech Transportation Institute (VTTI), proposed the evaluation of a microwave roadside animal detection system (ADS) in naturalistic conditions. To achieve this objective, a 300-meter-long buried dual-cable sensor system was installed and tested at a suitable location on the Virginia Smart Road where wild animals such as deer and bear, are often observed in a roadside environment. The buried sensor can detect the crossing of large and medium-sized animals when a generated electromagnetic detection field is perturbed and provides data on their location along the length of the cable. Target animals are sensed based on their electrical conductivity, size, and movement, with multiple simultaneous intrusions being detected during a crossing event. Data analyses indicated that the ADS, if properly installed and calibrated, is capable of detecting animals such as deer and bear with over 90% reliability. The ADS also performed well even when covered by 3 feet of snow and under various traffic conditions, showing no vehicle interferences during the same monitoring period. It is envisioned that the real-time crossing data acquisition can be used to improve highway safety through driver warning systems installed along roadway sections where high wildlife activity has been observed.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ABJ50 Standing Committee on Information Systems and Technology.
• Authors:
  • Druta, Cristian
  • Alden, Andrew S
  • Donaldson, Bridget M
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; References; Tables;
• Pagination: 15p

Subject/Index Terms

• TRT Terms: Animal vehicle crashes; Cables; Deer; Detection and identification technologies; Evaluation; Highway safety; Roadside fauna; Sensors; Warning systems; Wildlife
• Identifier Terms: Virginia Department of Transportation; Virginia Tech University
• Geographic Terms: Virginia
• Subject Areas: Data and Information Technology; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01659942
• Record Type: Publication
• Report/Paper Numbers: 18-00437
• Files: TRIS, TRB, ATRI
• Created Date: Feb 13 2018 9:53AM