Nauto® – Leader in fleet safety management, saving billions with significant in-vehicle innovation

The Silicon Review

Fleet management is the process that allows managing all fleet and asset information. This provides space to companies to reduce costs, improve efficiency, and ensure compliance across an entire fleet operation. Fleet Management may include various functions, such as leasing and financing of vehicles, vehicle maintenance, licenses and compliance, supply chain management, accident management, monitoring and diagnosis, driver management, speed management, fuel management, health, and safety management. Fleet management is a function that allows companies that depend on transportation in companies to eliminate or minimize the risks associated with an investment in vehicles, improve efficiency, productivity and reduce their overall transportation and personnel costs, providing compliance 100% of government legislation (duty of care) and many more.

Nauto^® is the only real-time, AI-enabled driver and fleet safety platform to predict, actively prevent, and reduce high-risk events in the mobility ecosystem. By analyzing billions of data points from over 800 million AI-analyzed video miles, Nauto's machine learning algorithms continuously improve driver behavior before events happen, not after. Nauto has enabled the largest commercial fleets in the world to avoid more than 45,000 collisions, resulting in nearly $200 million in savings.

Market-leading technologies and products furnished by Nauto^®

Multi-Tasked Convolutional Neural Networks

Nauto's proprietary AI and data analytics models are designed to simultaneously synthesize critical inputs to identify and alert drivers of imminent collisions in real-time. Your safest drivers are continually scanning the road for imminent risks. Predictive Collision Alerts can help all of your drivers anticipate risks caused by other drivers, cyclists, pedestrians, changing lights, etc. In-vehicle alerts should be smart. Predictive Collision Alerts are designed to take active braking, vehicle speed, and another vehicle movement to alert drivers when it matters most. Predictive Collision Alerts could give drivers as much as 100 extra feet to react to a potential collision when traveling 60 mph. Finally, Predictive Collision Alerts are designed to improve over time as Nauto's multi-task Convolutional Neural Networks model evolve and learn from critical contextual data. Nauto continuously synthesizes inputs from in and around the vehicle to determine levels of collision risk. As the detected threat intensifies, Predictive Collision Alerts signal the driver to take action with increasing levels of urgency. Simultaneously fuses driver behavior, vehicle movement, traffic elements, and contextual data to help predict and prevent collisions.

Real-time driver alerts and risk assessment

Driver distraction and drowsiness continuously process images from the interior sensor to analyze facial movements and detect unsafe driver behavior in real-time. Its embedded deep learning AI system is designed to identify vehicles on the road ahead and calculates the time to headway to help detect dangerous tailgating behavior. GPS sensor analysis monitors vehicle activity to help detect speeding over fleet-defined limits. IMU sensor analysis monitors vehicle activity to detect harsh vehicle maneuvers, such as acceleration, braking, and cornering.

Incident Reporting

Non-collision events can also lead to significant levels of g-force, which can result in false-positives in fleet solutions that use g-force as the only collision indicator. As a result, the firm set out to develop an edge-to-cloud machine learning model, a subset of artificial intelligence (AI), that uses the sensor data surrounding an event to detect actual collisions with a high confidence level all in real-time. Nauto's collision detection starts with a g-force value as the initial indicator that a collision may have occurred. From there, the on-device AI collision detection model analyzes the sensor data from before, during, and after the event to produce a confidence level for the likelihood of an actual collision, all in real-time on the Nauto Device.

The Visionary Leader behind the Success of Nauto^®

Dr. Stefan Heck is the Founder and also serves as the Chief Executive Officer of Nauto^®. Before Nauto, Dr. Heck was a Consulting Professor at the Precourt Institute for Energy at Stanford University. Previously he was a Senior Partner at McKinsey and co-founded and led the Cleantech and Sustainability practice. Dr. Heck earned a Ph.D. in Cognitive Science from UCSD and a B.S. with honors in Symbolic Systems from Stanford University.