Nvidia Corporation

Tai-Yuen Chan

David Nister

Gary D Hicok

Karl Friedrich Greb

John George Mathieson

Ram Ganapathi

Jonathan Sweedler

Ashok Srinivasan

Clement Farabet

Mohammed Abdulla Yousuf

Michael Truog

Michael Alan Ditty

Daniel Stewart Perrin

Kevin Flory

Dan Hettena

Autonomous driving is one of the world's most challenging computational problems. Very large amounts of data from cameras, RADARs, LIDARs, and HD-Maps must be processed to generate commands to control the car safely and comfortably in real-time. This challenging task requires a dedicated supercomputer that is energy-efficient and low-power, complex high-performance software, and breakthroughs in deep learning AI algorithms. To meet this task, the present technology provides advanced systems and methods that facilitate autonomous driving functionality, including a platform for autonomous driving Levels 3, 4, and/or 5. In preferred embodiments, the technology provides an end-to-end platform with a flexible architecture, including an architecture for autonomous vehicles that leverages computer vision and known ADAS techniques, providing diversity and redundancy, and meeting functional safety standards. The technology provides for a faster, more reliable, safer, energy-efficient and space-efficient System-on-a-Chip, which may be integrated into a flexible, expandable platform that enables a wide-range of autonomous vehicles, including cars, taxis, trucks, and buses, as well as watercraft and aircraft.

Systems and methods for safe and reliable autonomous vehicles

Growing community of inventors

San Jose, CA, United States of America

Tai-Yuen Chan