Physical AI Takes the Wheel: How the World’s Robotaxi Leaders Are Building With NVIDIA Technologies
NVIDIA details a three-computer robotaxi platform that Uber, Lyft, May Mobility, Mercedes-Benz and others are adopting to scale autonomous fleets.
NVIDIA says every major commercial robotaxi program runs on its stack, spanning training (DGX with Alpamayo VLA models), simulation and validation (Omniverse, Cosmos, AlpaSim on RTX PRO), and in-vehicle compute (DRIVE Hyperion 10 with dual DRIVE AGX Thor chips). Adding meta-action and chain-of-thought reasoning data to a VLA model reduced minimum average displacement error by 43%, from 2.08 to 1.18. Uber plans NVIDIA DRIVE Hyperion-based fleets across 28 cities by 2028, partnering with Autobrains, Avride, Lucid, May Mobility, Mercedes-Benz, Momenta, Nissan, Nuro, Pony.ai, Stellantis, Waabi, Wayve, WeRide and Zoox. DRIVE Hyperion 10 combines 14 cameras, nine radars, three lidars and 12 ultrasonics with redundant compute and NVIDIA Halos safety validation.
- NVIDIA claims all commercial-scale robotaxi programs run on its training, simulation, or in-vehicle stack.
- Robotaxi market projected to reach $400 billion by 2035 with over 6 million commercial vehicles.
- Uber plans DRIVE Hyperion fleets in 28 cities by 2028 plus a joint robotaxi AI data factory on Cosmos.
- Reasoning data cut a VLA model's trajectory prediction error by 43% (2.08 to 1.18) on an AV benchmark.
From the original article
6 min read at blogs.nvidia.com
The global robotaxi market — physical AI’s first commercial breakthrough — is projected to reach $400 billion by 2035, with over 6 million commercial vehicles in operation as driverless fleets are already moving people through some of the world’s busiest and most complex streets. Deploying a driverless vehicle is one challenge. Scaling a fleet is […]
By Ali Kani · blogs.nvidia.com
A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.