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公开(公告)号：US20190258251A1
公开(公告)日：2019-08-22
申请号：US16186473
申请日：2018-11-09
Applicant: NVIDIA Corporation
Inventor： Michael Alan DITTY , Gary HICOK , Jonathan SWEEDLER , Clement FARABET , Mohammed Abdulla YOUSUF , Tai-Yuen CHAN , Ram GANAPATHI , Ashok SRINIVASAN , Michael Rod TRUOG , Karl GREB , John George MATHIESON , David Nister , Kevin Flory , Daniel Perrin , Dan Hettena
Abstract: 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.
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公开(公告)号：US20240045426A1
公开(公告)日：2024-02-08
申请号：US18143360
申请日：2023-05-04
Applicant: NVIDIA Corporation
Inventor： Michael Alan DITTY , Gary HICOK , Jonathan SWEEDLER , Clement FARABET , Mohammed Abdulla YOUSUF , Tai-Yuen CHAN , Ram GANAPATHI , Ashok SRINIVASAN , Michael Rod TRUOG , Karl GREB , John George MATHIESON , David NISTER , Kevin FLORY , Daniel PERRIN , Dan HETTENA
CPC classification number: G05D1/0088 , G05D1/0248 , G05D1/0274 , G06F15/7807 , G06N3/063 , G06V20/58 , G06V20/588 , G05D2201/0213 , G06N3/045
Abstract: 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.
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公开(公告)号：US20230176577A1
公开(公告)日：2023-06-08
申请号：US18076543
申请日：2022-12-07
Applicant: NVIDIA Corporation
Inventor： Michael Alan DITTY , Gary HICOK , Jonathan SWEEDLER , Clement FARABET , Mohammed Abdulla YOUSUF , Tai-Yuen CHAN , Ram GANAPATHI , Ashok SRINIVASAN , Michael Rod TRUOG , Karl GREB , John George MATHIESON , David NISTER , Kevin FLORY , Daniel PERRIN , Dan HETTENA
CPC classification number: G05D1/0088 , G05D1/0248 , G05D1/0274 , G06F15/7807 , G06N3/063 , G06V20/58 , G06V20/588 , G05D2201/0213 , G06N3/045
Abstract: 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.
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