Researchers collected data from more than 10,000 passing vehicles. The study measured animal-detection accuracy and driver speed, but it did not directly establish whether the system prevented collisions or fatalities. The pilot was sponsored by the Virginia Department of Transportation and conducted as part of VDOT’s expansion of Corridor Q, which extends Route 460 from the Kentucky state line to Grundy.

The wider corridor traverses portions of Kentucky, Virginia and West Virginia as part of the Appalachian Development Highway System and is home to approximately 100 elk. A feasibility study associated with the project estimated that elk collisions cost more than $80,000 per crash on average. Adult male elk can weigh between 550 and 1,300 pounds.

VTTI research scientist Jean Paul Talledo Vilela said the project was intended to reduce the risk of accidents and fatalities while protecting elk within their habitat. The location also presented technical challenges because reliable wildlife detection and communication had to function in remote, mountainous terrain. At the 750-meter test site, the team installed eight portable, solar-powered trailers equipped with thermal cameras.

The cameras continuously monitored the roadway and adjacent shoulder areas for medium- and large-sized wildlife, while AI software analyzed the camera feeds. When wildlife was detected, nearby dynamic message signs displayed a warning that wildlife had been detected ahead and instructed approaching motorists to slow down. Crosstek supplied the cameras and off-the-shelf wildlife-detection software, while T-Mobile’s 5G cellular network and satellite service supported remote monitoring and data communications.

The system achieved 97 percent overall accuracy in identifying medium- and large-sized wildlife during deployment. Talledo Vilela said the units needed to communicate with one another and relay information to the main hub despite difficult topography. Their portable, solar-powered design was also intended to withstand local weather conditions.

Roadside radar units measured vehicle speeds to determine whether drivers responded to the electronic warnings. The initial analysis found an average speed reduction of 3 mph as vehicles approached signs that had been activated by wildlife detections. “Speed is an important data point to understand if drivers were actually paying attention to the message board,” Talledo Vilela said, noting that a modest reduction may indicate increased attention to surroundings even when drivers do not brake sharply. VTTI research associate Shreyas Bhat said the project demonstrated an automated system capable of detecting wildlife, activating real-time warnings and producing measurable changes in driver behavior at warning signs and across the broader detection corridor.

The pilot ended in September 2026, and data analysis was continuing. The project’s remote-data-management approach received first place in the Innovation in Community category of the 2026 T-Mobile Innovate Awards. The team said further analysis would help assess how the portable system could be transferred to other locations where wildlife frequently crosses roads, while also exploring adaptation for other real-time roadway hazards.

Subject of Research: Pilot evaluation of automated wildlife detection and real-time driver warnings on Virginia Route 460

Article Title: Real-time driver warning system helps prevent animal collisions

Article References: Real-time driver warning system helps prevent animal collisions. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: wildlife detection, driver warnings, thermal cameras, artificial intelligence, elk crossings, driver speed, road safety, Appalachian highways, smart transportation, field pilot, Real-time, driver