Lucid, Uber and Nuro Unveil Global Robotaxi at CES, Announce Autonomous On-Road Testing

On January 5, 2026, Lucid Group, Nuro, and Uber revealed the production-intent vehicles that will power their upcoming global robotaxi service and debuted the Uber-designed in-cabin rider experience at CES 2026.

The companies also confirmed that autonomous on-road testing began last month, marking a major milestone ahead of the service’s planned launch in the San Francisco Bay Area later this year. Testing is being led by Nuro using robotaxi engineering prototypes operated under the supervision of trained autonomous vehicle operators, starting in the Bay Area.

“The debut of our production intent robotaxi with Lucid and Uber is a significant milestone on our path to delivering autonomy at scale,” said Dave Ferguson, Co-Founder and Co-CEO of Nuro. “By bringing together Nuro’s proven level 4 autonomy, Lucid’s advanced vehicle architecture, and Uber’s global reach, we’re building a robotaxi service designed for real-world operations and long-term growth.”

CES attendees are getting a first look at both the robotaxi and the in-cabin experience. The vehicle is based on the all-electric Lucid Gravity and features a next-generation sensor suite with high-resolution cameras, solid-state lidar, and radar providing full 360-degree perception. The sensors are seamlessly integrated into the vehicle body and a low-profile, purpose-built roof-mounted halo designed to preserve Lucid’s signature design. Integrated LED lighting in the halo helps riders identify the correct vehicle, displays rider initials, and communicates trip status from pickup through drop-off.

“Uber is proud to partner with Lucid and Nuro to bring a state-of-the-art robotaxi to market later this year,” said Sarfraz Maredia, Global Head of Autonomous Mobility & Delivery at Uber. “By combining leading expertise in electric vehicles, autonomy, and ridehailing, we’re building a unique new option for affordable and scalable autonomous rides in the San Francisco Bay Area and beyond.”

Inside, the Uber-designed rider experience emphasizes comfort, transparency, and control. Interactive screens allow passengers to personalize their ride, adjust climate and seat settings, manage entertainment, contact support, or request a pull-over. Real-time visualizations show what the vehicle “sees” and how it plans its path, including lane changes, traffic light responses, pedestrian yielding, and passenger drop-off. The spacious interior accommodates up to six passengers with ample luggage capacity, positioning the robotaxi as a premium option for group travel.

“Our robotaxi program with Uber and Nuro is a key part of how Lucid is leveraging its technology to create a more sustainable future of mobility that is widely accessible,” said Kay Stepper, Vice President of ADAS and Autonomous at Lucid. “Our engineering, range and interior comfort offers a unique platform, and when combined with Nuro’s technology and Uber’s scale, we are collectively building an experience like no other.”

The vehicle’s autonomous system is powered by high-performance computing based on NVIDIA DRIVE AGX Thor, part of the NVIDIA DRIVE Hyperion platform. On-road testing is a core element of Nuro’s safety and validation framework, which also includes closed-course testing and large-scale simulation. The program evaluates dozens of capabilities across the autonomy stack, including Nuro’s end-to-end AI foundation model that combines advanced machine learning with verifiable safety logic.

Pending final validation, production-intent robotaxis are expected to begin manufacturing later this year at Lucid’s Arizona facility. The vehicle is on public display for CES attendees at NVIDIA’s showcase at the Fontainebleau Hotel from January 5 at 3:00 p.m. PT through January 8, 2026.

Lidar Safer than Camera-Only Robotaxis

Lidar, used by Lucid, Nuro and Uber, is widely viewed as a safer approach for robotaxi systems than relying on cameras alone because it delivers precise three-dimensional perception, performs reliably in low-light and challenging environments, and adds critical redundancy. Lidar can detect pedestrians and obstacles in conditions such as glare, dust, or darkness where camera-based systems often struggle. While some companies continue to pursue vision-only strategies, most autonomous vehicle developers favor sensor fusion as the safest path forward.

Lidar enhances safety by generating highly accurate 3D point clouds that provide exact distance and shape information, rather than the two-dimensional imagery produced by cameras. Because it does not depend on visible light, lidar remains effective at night and is less impacted by sun glare, shadows, or certain adverse weather conditions. When combined with cameras and radar, lidar creates a layered sensing system that ensures objects are detected even if one sensor type is compromised. In real-world testing, companies such as Waymo have demonstrated earlier and more reliable detection of pedestrians and obstacles in difficult conditions using this approach.

Advocates of camera-only systems, most notably Tesla, argue that cameras replicate human vision and that advanced artificial intelligence can achieve full autonomy without lidar. This approach reduces system cost and complexity but faces serious limitations in extreme lighting and weather scenarios where visual perception degrades.

Across the industry, companies pursuing Level 4 and Level 5 autonomy, including Waymo and Zoox, largely agree that combining cameras, radar, and lidar provides a more robust and reliable sensing stack. This multi-sensor strategy is designed to exceed human perception and deliver consistent safety across all environments.

In practice, while cost-saving vision-only systems continue to evolve, lidar remains a critical safety layer for most robotaxi developers, offering dependable depth perception and redundancy that cameras alone cannot consistently provide in real-world operating conditions.

If your’e riding in robotaxis or investing in them, we recommend the Lidar systems and advise avoiding the camera-only systems.