Nauto edges AI dash cam competitors in VTTI benchmark study
April 2, 2025
The Virginia Tech Transportation Institute worked to mirror their 2023 study benchmarking Motive, Lytx, and Samsara’s safety solutions. Nauto's tech came out on top in terms of detection speed and accuracy.
The 2024 study tested Nauto’s alert performance for six risky driving behaviors in a heavy truck, including:
Texting
Using a phone in a driver’s lap
Taking a phone call
Rolling stops
Close following
Seatbelt usage.
Specifically, VTTI found that Nauto was 100% successful at providing in-cab alerts for distraction or poor driver behavior, with an average time of 3.8 seconds to alert a driver.
VTTI also found that Nauto accurately detected texting, phone usage in a driver’s lap, a driver placing a call, and seatbelt usage 100% of the time, day or night. It detected rolling stops 100% accurately during the day, and 90% accurately at night, and caught close following at a rate of 40% accuracy during the daytime and 60% at night, potentially due to how the device was inaccurately set up.
The test for "close following" was tainted by improper device setup, so VTTI plans to redo that one and release the results at a later date.
Overall, the latest study also found that Nauto was the fastest system at detecting each behavior, with Motive’s alerts coming not long afterwards. The ‘Close Following’ category is the only exception, where Lytx’s 2023 TTA was faster by 2.48 seconds. This result is being retested due to the 2024 test’s setup.
On a granular level, Nauto’s TTA for texting was 3.57 seconds, faster than Motive’s time in 2023 of 6.89 seconds. The system sounded an alarm for phone usage in the lap after 3.23 seconds, and outgoing calls after 4.7 seconds. Finally, Nauto’s TTA for no seatbelt was 13 seconds.
For vehicle behavior, Nauto provided rolling stop alarms at 3.4 seconds and close following at 15.5 seconds.
"VTTI’s 2024 study underscores Nauto’s position as the alert accuracy and time-to-alert performance leader in AI-powered fleet safety technology," said Dr. Stefan Heck, CEO of Nauto. "Nauto’s ability to significantly deliver faster, more accurate alerts gives drivers critical time to react and helps prevent accidents. By alerting drivers to take action and return their focus to the road faster than other systems, Nauto helps drivers get home safely and has the potential to cut in half the number of collisions and potential fatalities on our roadways.”
The company emphasized the importance of quick, accurate alerts due to how far a truck can travel at highway speeds in seconds and how safety systems need to retain driver trust to be effective.
The study setup
VTTI tested Nauto’s AI-powered system in December 2024. The study was commissioned by Nauto and designed to mimic the testing conditions and protocols for the AI Dash Cam Performance Benchmark Testing, which took place in June 2023.
The test used the same VTTI dash cam assessment protocol in both studies and evaluated Nauto’s performance by calculating the rates of in-cabin audible alerts, the rate of alerts recorded on Nauto’s virtual platform dashboard, and the time to alert (TTA) from the start of a specific driving behavior or from the time to collision.
The program tested five driver maneuvers in a single location during both bright and dark lighting conditions, with 10 replications per day/nighttime testing, according to the company. Specifically, the study worked in good weather on dry roadways and used the same VTTI researcher as a driver for each test. The study also used the same vehicle model for each run. One small difference between 2024 and 2023’s tests is that Nauto’s study only had one installation location, while 2023’s rotated each safety system through three positions on the vehicle.
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.
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