VTTI study finds Nauto technology boosts safety for distracted drivers

The study measured the accuracy of Nauto’s alerts and if the AI-powered system properly monitored and warned distracted drivers before their alert counterparts.

Alex Keenan

Related To:

Nauto

Nov. 10, 2025

4 min read

Key Highlights

At the end of 2024, Nauto commissioned the Virginia Tech Transportation Institute to test its Prdictive Risk Fusion system
The AI-powered system was designed to monitor multiple collision risks at once, such as speeding combined with texting and an impending collision
VTTI reported that the system did alert distracted drivers 10% faster when approaching a stopped vehicle than alert ones, with an average time to alert of 3.8 seconds

According to third-party testing done by Virginia Tech Transportation Institute (VTTI), Nauto's Preditive Risk Fusion was proven to enhance alert times in distracted driving scenarios. Predictive Risk Fusion combines real-time in-cab driver monitoring with external road hazard detection.

Key findings included a 90% in-cab alert success rate when approaching a target, with 87% of alerts delivered before reaching "the swerve zone," or the point where drivers can steer out of a collision.

The study completed in December 2024 also found the monitoring technology provided distracted drivers with a 10% faster alert speed to prevent a collision with a stationary object.

This data suggests Nauto's predictive safety solution can help stem the tide of the distracted driving epidemic in the U.S, from which NHTSA attributed 3,275 fatalities and approximately 325,000 injuries. When it comes to mitigating crashes, every second counts.

"VTTI's latest research validates that Nauto's Predictive Risk Fusion technology doesn't just detect dangerous situations, it predicts them," said Dr. Stefan Heck, CEO of Nauto. "In real-world driving, every extra tenth of a second matters and translates into room for drivers to brake or swerve to avoid collisions. By simultaneously recognizing driver behaviors and external risks, we're giving drivers the extra time they need to stay safe and fleets a proven way to reduce losses and lower insurance costs."

Nauto’s Predictive Risk Fusion solution is meant to better understand how risk factors stack when a driver is on the road, including factors inside and outside the cab. For instance, when combining a driver looking down with speeding and a pedestrian crossing the road, Nauto said that this increases the risks of a collision by 2578 times more than normal. So, the Predictive Risk Fusion solution aims to provide earlier alerts than typical collision mitigation systems and before automatic emergency braking deploys, and the company commissioned VTTI to evaluate these alerts.

Study results

During the study, VTTI found that the Predictive Risk Fusion system alerted distracted drivers to a potential collision with a stopped car 10% faster than if they were not distracted, and 6% faster when there was a risk of hitting a pedestrian. More specifically, the system warned drivers faster while they were texting in two out of three tests, and in daylight hours, 75-100% of the alerts gave drivers time to swerve.

Nauto comparison of alert accuracy and time-to-alert

By direct comparison, when the system detected that the driver was texting, it was generally .2s faster to provide alerts with a potential collision, with the only exception when a distracted driver was approaching a motorcycle target. 88% of in-cab alerts were delivered prior to the swerve zone when the driver was distracted, with an average time to alert of 3.8 seconds for distracted behavior.

For both distracted and attentive drivers, VTTI reported that the system provided 80-100% successful alerts.

Study methodology

To test Nauto’s AI-powered system, VTTI ran tests where a vehicle equipped with the Predictive Risk Fusion technology approached a stopped car, motorcycle target, and a pedestrian in a light-duty commercial vehicle. Then it ran tests where the driver was both distracted and alert, and measured when the system responded to the driver’s distraction.

For the general testing environment, VTTI tested Nauto’s technology in five driver maneuvers with six risky driving behaviors. It then calculated rates of in-cabin alerts, rates of alerts recorded on the platform’s dashboard, and the time to alert from the start of the behavior or from the time to collision.

Additionally VTTI separated the rate of audible alerts for forward collision warning and pedestrian collision warnings, and also logged if warnings occurred before or after the swerve point, or after the target. The swerve point was set 35 ft. from the target so that a driver would have enough time to avoid the object if travelling at the test speed of 25 mph.

The tests took place in one place during both the day and night, with 10 repetitions per time of day. They also tested the technology in good weather with dry roadways, and all the trials had the same commercial driver.

About the Author

Alex Keenan

Alex Keenan is an Associate Editor for Fleet Maintenance magazine. She has written on a variety of topics for the past several years and recently joined the transportation industry, reviewing content covering technician challenges and breaking industry news. She holds a bachelor's degree in English from Colorado State University in Fort Collins, Colorado.