NVIDIA DRIVE - Safety
The next generation of transportation is autonomous. NVIDIA is leading the way, driven by a mission to develop self-driving technology that enables safer, less congested roads and mobility for all. Find out more about our vision, innovations, and processes with our NHTSA-based NVIDIA Self-Driving Car Safety Report submitted to the National Highway Traffic Safety Adminstration.
The Four Pillars of Safe Autonomous Driving
Safe autonomous driving is built on four fundamental pillars. With high-performance compute at their core, these tenets illustrate NVIDIA’s dedication to safety and ensure a robust self-driving technology development cycle.
Pillar 1: An Artificial Intelligence Design and Implementation Platform
A safe AI driver needs a compute platform that spans the entire range of autonomous driving—from assisted highway driving to robotaxis. This platform needs to combine deep learning, sensor fusion, and surround vision to enable the car to make split-second decisions based on massive amounts of data.
To safely operate, self-driving vehicles require supercomputers powerful enough to process all the sensor data in real time. Our underlying hardware solutions include:
- NVIDIA® Xavier™ architecture: DRIVE Xavier, World’s First Single-Chip Self-Driving Car Processor, Gets Approval from Top Safety Experts.
- NVIDIA Xavier development process: Making the Grade: NVIDIA Xavier Achieves Another Milestone for Safe Self-Driving
- NVIDIA Xavier safety assessment: NVIDIA Xavier Achieves Industry First with Expert Safety Assessment
For self-driving cars, processing performance translates to safety. The more compute, the more sophisticated the algorithm, the more layers in a deep neural network (DNN), and the greater number of simultaneous DNNs that can be run simultaneously. You can find an overview of our autonomous driving safety software policy here:
- Planning a Safer Path: Mathematically Proven and Validated in Simulation, NVIDIA Safety Force Field Protects Against Real-World Traffic
Pillar 2: Development Infrastructure That Supports Deep Learning
In addition to in-vehicle supercomputing hardware, NVIDIA solutions power the data centers used to solve critical challenges faced in the development of safe AVs. A single test vehicle can generate petabytes of data each year. Capturing, managing, and processing this massive amount of data for not just one car, but a fleet requires an entirely new computing architecture and infrastructure.
Pillar 3: Data Center Solution for Robust Simulation and Testing
The ability to test in a realistic simulation environment is essential to providing safe self-driving vehicles. By coupling actual road miles with simulated miles in a high-performance data center solution, manufacturers can comprehensively test and validate their technology.
Pillar 4: Best-in-Class, Pervasive Safety Program
Self-driving technology development must follow a pervasive safety methodology that emphasizes diversity and redundancy in the design, validation, verification, and lifetime support of the entire autonomous system. These programs should follow recommendations from federal and international agencies such as the National Highway Traffic Safety Administration, International Organization for Standardization, and the global New Car Assessment Program.