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Safety Is What Drives Us: Introducing the NVIDIA Self-Driving Safety Report

Autonomous vehicles promise to reduce traffic accidents by replacing unpredictable human drivers with artificial intelligence. But how do manufacturers ensure these new drivers are truly safe?

we are opening up our development processes. We show how we harness the unprecedented computing power of GPUs to create functionally safe self-driving systems. Achieving the highest levels of compute enables us to incorporate diversity and redundancy into every solution — from sensor types to processors to algorithms — ensuring there is never just one line of defense in the event of a failure.

As a solutions provider to the vast majority of vehicle makers, suppliers, sensor makers, startups and mapping companies in the autonomous driving space, NVIDIA makes safety our first priority. And we have integrated it into every step of the development process.

We believe safety is at the heart of the transition to autonomy. Our report details how compute performance translates to safety at all stages, from initial data collection to public road testing.

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 requires a compute platform that spans the entire range of autonomous driving, from assisted highway driving to robotaxis. It must combine deep learning, sensor fusion and surround vision to enable the car to make split-second decisions based on massive amounts of data.

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Read More: Interview with Angel Gambino, CEO and Founder of Sensai

Pillar 2: Development Infrastructure That Supports Deep Learning

A single test vehicle can generate petabytes of data annually. 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.

Read More: Interview with Jeffrey Kofman, CEO and Founder at Trint

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.

Read More: The Top 5 “Recipes” That Give AI Projects a Higher Likelihood of Success

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