◼︎ Simultaneously fuses driver behavior, vehicle movement, traffic elements, and contextual data to help predict and prevent collisions
◼︎ Helps reduce rear-end collisions, the most frequent road incident, accounting for an average 26% of total fleet losses at $82,000 per incident
◼︎ Provides distracted drivers with twice as much reaction time to prevent collisions than traditional forward collision warning (FCW) systems
PALO ALTO, Calif., May 14, 2020 — Nauto®, a leading provider of AI-powered fleet and driver safety products, today announced Predictive Collision Alerts, a new module in its Driver Behavior Learning Platform. The new offering is designed to detect imminent collisions to help reduce rear-end accidents by up to 400% more than traditional approaches.
Until now, fleet and driver safety products, called “video telematics” systems, have been focused on driver coaching and fleet management applications. “We evaluated multiple AI-powered products to support our commitment to driver safety,” said Greg McLeod, Pepin. “Nauto’s distracted driver detection was vastly superior to others because it isn’t simply a learning tool--it actively enables drivers to avoid collisions before they happen. We expect Predictive Collision Alerts to further reduce our number of rear-end collisions.”
Nauto Predictive Collision Alerts works like the human brain. It continuously synthesizes inputs from in and around the vehicle, including driver behavior, vehicle movement, traffic elements, and contextual data, in its multi-tasked Convolutional Neural Networks (CNN) model to determine levels of collision risk. As the detected risk intensifies, Predictive Collision Alerts signals the driver to take action with increasing levels of urgent alerts.
The initial implementation of Predictive Collision Alerts will focus on reducing rear-end incidents—which account for an average of 26% of total fleet losses at $82,000 per incident. Before Nauto’s technology, fleet managers’ only options were costly, difficult-to-install, aftermarket forward collision warning (FCW) systems. FCW systems use rudimentary physics—calculations based on lead and trailing vehicles speed, time, and distance—to deliver warnings. They cannot provide the extra warning time needed to account for driver inattention and contextual data. Only Nauto’s Predictive Collision Alerts leverages multi-tasked CNN models to provide drivers up to two times more warning time than traditional FCW systems.
“What if you had 100% more time to make a life-or-death decision and take corrective action?” said Shweta Shrivastava, chief product officer, Nauto. “With more than 650 million AI-processed miles informing our platform, Nauto already leads the way in providing real-time training that helps drivers adjust behavior and avoid collisions in the moment. Traveling at 60 miles per hour, our new Predictive Collision Alerts could give drivers as much as 100 extra feet to react to a potential collision. This product will save lives.”
Nauto’s Predictive Collision Alerts were demonstrated at an exclusive customer event on May 13 and will be available for order this June.
Nauto® is the only real-time AI-powered Driver Behavior Learning Platform able to help predict, prevent, and reduce high-risk events in the mobility ecosystem. By analyzing billions of data points from over 525 million AI-analyzed video miles, Nauto’s machine learning algorithms continuously improve and help to impact driver behavior before events happen, not after. Nauto has enabled the largest commercial fleets in the world to avoid more than 25,000 collisions, resulting in nearly $180 million in savings.