Uber is set to revolutionize its transportation services by partnering with Nvidia to introduce a fleet of 100,000 autonomous vehicles by 2027. This collaboration, announced at Nvidia’s GTC conference in Washington, DC, aims to make self-driving cars a mainstream option on Uber’s platform. The expansion will leverage Nvidia’s cutting-edge artificial intelligence systems and hardware, building on a previous agreement where Uber shared driving data to enhance Nvidia’s AI models.
Nvidia introduced the Nvidia Drive AGX Hyperion 10 platform at the event, enabling car manufacturers to equip vehicles with the necessary hardware, sensors, and software for safe autonomous driving. Stellantis NV, known for brands like Jeep and Peugeot, will supply at least 5,000 Nvidia-powered robotaxis for Uber’s fleet in the US and select international markets, with Foxconn assisting in production starting in 2028. Uber will oversee all aspects of the vehicles post-deployment, including remote assistance, maintenance, and customer service.
Although full-scale production is a few years away, pilot programs and testing will commence soon, leading to the ambitious goal of 100,000 autonomous vehicles by the end of the decade. This move is expected to significantly reduce operational costs for Uber and provide greater control over the fleet experience. While Uber currently relies on gig workers, transitioning to robotaxis could enhance profitability if the technology proves viable and regulators support the shift.
Uber’s existing autonomous ride offerings in cities like Austin and Atlanta will be expanded through the Nvidia partnership, increasing access to a broader network of autonomous developers. The 100,000-vehicle target includes cars from previous partnerships and contributions from various developers. The collaboration will also focus on establishing a “robotaxi data factory” to enhance driverless systems by collecting driving data for training AI models.
Uber and Nvidia aim to create a robust data engine for automation, streamlining the path to profitable autonomy deployment through data collection, labeling, scenario mining, and large-scale training. This strategic alliance signals a significant step towards reshaping the future of ride-hailing services with autonomous vehicles.