Colorado Traffic and Animal Detection (COTAD) Model - Training the YOLO algorithm to Reliably Detect Colorado Wildlife, Pedestrians, and Vehicles

Reliable, automated detection of wildlife in real-time from optical and thermal camera images, and using detection to alert drivers by using dynamic wildlife warning signs (DWW), can save lives and protect property, as well as protect wildlife. This research will develop and train COTAD to detect Colorado large wildlife and test the algorithm near highways. If successful and paired with DWW, this project could become a highly used and cost effective tool to continue Colorado Department of Transportation's (CDOT’s) progress and leadership in reducing wildlife-vehicle collisions.

Language

• English

Project

• Status: Programmed
• Funding: $283,000.00
• Sponsor Organizations:

  Colorado Department of Transportation

  Applied Research and Innovation Branch
  Denver, CO  United States  80204
• Project Managers:

  Roeder, Bryan

• Start Date: 20251223
• Expected Completion Date: 20300630
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Algorithms; Detection and identification systems; Warning signs; Wildlife
• Geographic Terms: Colorado
• Subject Areas: Data and Information Technology; Environment; Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01975083
• Record Type: Research project
• Source Agency: Colorado Department of Transportation
• Files: RIP, STATEDOT
• Created Date: Dec 23 2025 1:50PM