Wayve and Nissan to exhibit global robotaxi prototype vehicle powered by NVIDIA DRIVE Hyperion for Uber trials

Published: March 16, 2026

Location: TOKYO, JAPAN

© 2026 Nissan North America, Inc.

TOKYO and SUNNYVALE – Wayve and Nissan will exhibit a global robotaxi prototype vehicle at NVIDIA GTC 2026, built on the NVIDIA DRIVE Hyperion platform. This exhibit follows the recent announcement by Wayve, Nissan and Uber of plans to collaborate on a robotaxi pilot deployment in Tokyo beginning in late 2026, subject to discussions with relevant authorities. This prototype vehicle will be used in this pilot program. A Global Robotaxi Vehicle Built on the all-electric Nissan LEAF, this robotaxi prototype vehicle combines Nissan’s vehicle engineering, Wayve’s embodied AI software, and NVIDIA DRIVE Hyperion. Nissan is developing a vehicle with fully redundant systems designed for robotaxi. The integration of the Wayve AI Driver builds on the ongoing collaboration between Nissan and Wayve to bring the AI Driver into Nissan’s state-of-the-art vehicle platform, helping accelerate development toward a scalable robotaxi platform. The vehicle is built on DRIVE Hyperion reference compute and sensor architecture, designed for Level autonomy. It features dual NVIDIA DRIVE AGX Thor processors, delivering the performance required to run advanced AI models in real time while meeting automotive safety standards. The system runs on NVIDIA DriveOS and is supported by NVIDIA Halos, NVIDIA’s framework for functional safety and cybersecurity. Sensor Suite and Vehicle Platform The Nissan LEAF-based prototype features a comprehensive sensor suite designed for full visibility and redundancy, including high-resolution cameras providing 360-degree coverage, high-performance surround and forward imaging radar, and a forward-facing LiDAR that provides complementary sensing to support the AI Driver’s scene understanding and decision-making. The platform also supports additional long-range sensing to enable data collection, validation, and other development use cases. Nissan will further refine it for robotaxi use, including features such as intuitive in-cabin displays and communication systems to support the rider experience. Wayve AI Driver Wayve’s AI Driver uses end-to-end embodied AI to enable autonomous driving. It processes data from onboard sensors to understand complex traffic environments and make safe driving decisions in real time. The system does not rely on HD maps; instead, it learns how traffic situations evolve and anticipates the impact of its actions on surrounding road users, allowing it to operate smoothly and safely in dynamic conditions. Supporting Global Robotaxi Deployment Wayve and Uber plan to expand robotaxi trials to more than 10 cities globally, with vehicles introduced in select markets as deployment progresses. As validation continues, the companies aim to move from pilots with safety operators to scalable robotaxi services designed for long-term deployment.

Quick Q&A

Who are the primary organizations involved in this announcement?

Wayve, Nissan, and Uber are collaborating on this robotaxi initiative.

What was announced regarding the robotaxi prototype vehicle?

Wayve and Nissan will exhibit a global robotaxi prototype vehicle at NVIDIA GTC 2026, which is built on the NVIDIA DRIVE Hyperion platform.

When is the robotaxi pilot deployment in Tokyo planned to begin?

The robotaxi pilot deployment in Tokyo is planned to begin in late 2026, subject to discussions with relevant authorities.

Why is the NVIDIA DRIVE Hyperion platform significant for this robotaxi prototype?

The NVIDIA DRIVE Hyperion platform provides the reference compute and sensor architecture, including dual NVIDIA DRIVE AGX Thor processors, essential for running advanced AI models in real time and meeting automotive safety standards.

What are the future implications for Wayve and Uber's robotaxi trials?

Wayve and Uber plan to expand robotaxi trials to more than 10 cities globally, aiming to move from pilots with safety operators to scalable robotaxi services for long-term deployment.

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