Motive launched a new set of AI Driver Safety tools aimed at helping fleets detect fatigue, distracted driving and low-severity collisions.

The new products come to market at a time when fatigue alone accounts for over 100,000 crashes, 800 deaths, and 50,000 injuries annually, Motive says, adding that it is important to spot high-risk driver behaviors earlier.

“Distraction and fatigue are among the most preventable causes of collisions, but they’re also the hardest to catch early,” said Hemant Banavar, chief product officer at Motive. “The risk shows up first in subtle behaviors, like eye rubbing or small lapses in attention, that most systems miss. Motive detects those signals in real-time and filters out false positives, so teams can act on real risk before it turns into a collision.”

Fatigue, eating detection

An AI-powered fatigue detection system is available on the dashcams and does not require additional hardware. The feature connects six key indicators, including face rubbing, stretching, eye rubbing, yawning, lane swerving, and microsleep, to detect fatigue early and get drivers off the road before a collision occurs.

On-device AIdelivers real-time, in-cab alerts so drivers can take action immediately. Meanwhile, safety teams can see all behaviors on a single event timeline with context such as drive time and historical fatigue trend in the Motive Dashboard.

Meanwhile, Motive says that eating behind the wheel can also double the risks, with more than half of the drivers admitting to doing that. To address that, Motive launched a feature which identifies active eating behavior when food is visible in a driver’s hand or mouth and eating lasts at least five seconds.

Detecting minor collisions

Motive also claims that traditional telematics often miss low-severity collisions such as sideswipes and fender benders, delaying incident response and increasing liability. The company says its new AI-powered detection tool combines telematics with computer vision to accurately detect more collisions across all severity levels, while avoiding false positives. It captures incidents within the camera’s view, such as light rear-end collisions, fast sideswipes, and minor bumper taps or scrapes in tight spaces or traffic. Managers receive real-time alerts with video and telematics data to resolve claims faster, exonerate drivers, and better protect their organizations.