If you happen to see a Lucid Gravity SUV adorned with sensors cruising through San Francisco, it's likely part of the latest innovation from Uber and Nuro. Selected Uber employees now have the opportunity to request rides in this advanced robotaxi through the Uber app, marking a significant step towards a broader public launch anticipated later this year.
Nuro announced this development in a recent blog post, confirming that the vehicles are operating autonomously with a human safety operator present as a precaution. This initiative follows the companies' partnership formed in July 2025, which included a substantial investment from Uber amounting to $300 million in Lucid, alongside a commitment to purchase "at least" 20,000 of their new Gravity SUVs over the next six years.
The Lucid Gravity robotaxi is equipped with Nuro's autonomous driving system, powered by Nvidia's Drive AGX Thor computer. These vehicles feature high-resolution cameras, solid-state lidar sensors, and radar technology, enabling them to accurately perceive and navigate their environments.
In addition to its investment in Lucid, Uber has also contributed a significant, undisclosed amount to Nuro. The plan is for Uber to manage and operate this premium robotaxi service, potentially with assistance from a third party. Production of the modified Lucid Gravity vehicles is expected to commence in late 2026, as outlined in a regulatory filing from the previous year.
Nuro has already made strides in testing, having completed closed-course evaluations and initiated public road trials with the autonomous Lucid Gravity SUVs late last year. Currently, Nuro's engineering fleet comprises 100 Lucid Gravity SUVs equipped with the self-driving technology, which are utilized to gather real-world data and refine autonomous driving capabilities across various U.S. locations.
The ongoing employee test rides are crucial for assessing how the vehicle's autonomy, design, and user experience integrate in real-world conditions. This testing phase is vital for understanding how effectively the robotaxis can manage the complexities of rider pickups and drop-offs, a challenging aspect of autonomous ride-hailing.