Robotaxi services from 2027
How Nvidia is turning AI into road-ready autonomy
In the new CLA, Mercedes-Benz deploys substantial Nvidia computing power to enable advanced ADAS functionalities.
Mercedes-Benz
Nvidia is moving beyond chips and simulations to position itself as a central force in autonomous mobility. A robotaxi service is planned for 2027, while passenger vehicles equipped with the platform are expected to follow from 2028.
Nvidia is pushing deeper into autonomous mobility, aiming to
translate its dominance in artificial intelligence into large-scale, real-world
deployment on public roads. CEO Jensen Huang outlined a roadmap that goes well
beyond supplying computing hardware: Nvidia intends to help launch a robotaxi service as early as 2027, followed
by the introduction of AI-driven systems in privately owned vehicles between
2028 and 2030.
According to the company, the core ambition is to enable
vehicles that do more than detect objects. Instead, AI systems are designed to
interpret traffic situations in context, anticipate potential developments and
make decisions in a way that resembles human reasoning. Nvidia sees this
capability as a prerequisite for scaling autonomous driving safely and
economically.
From demonstration vehicles to urban deployment
Ahead of the 2026 Consumer Electronics Show (CES) in Las
Vegas, Nvidia showcased the current maturity of its technology together with
Mercedes-Benz. A production version of the new Mercedes CLA navigated public
roads in San Francisco, following traffic rules, responding to traffic lights
and signs, and interacting with pedestrians. Over a test route of roughly 45
minutes, a safety driver intervened only in a handful of situations.
The vehicle relied on a sensor configuration combining ten
cameras and five radar units. For future robotaxi applications, Nvidia plans to
extend this setup with lidar sensors to improve
environmental perception in dense urban scenarios. This multi-sensor
strategy stands in contrast to approaches that rely exclusively on cameras,
underlining Nvidia’s focus on redundancy and robustness rather than minimal
hardware.
Intensifying competition in the robotaxi market
The race to deploy driverless services is accelerating.
Google subsidiary Waymo currently operates around 2,500 fully autonomous
vehicles across several US cities, making it the most advanced player in
commercial robotaxi operations. Its position has been further underlined since
2025, when Waymo began expanding its technology
partnerships, including a preliminary agreement with Toyota Motor Corporation
to explore closer collaboration on accelerating
autonomous driving development. The move signalled Waymo’s intention to
scale its technology beyond proprietary fleets and into broader automotive
ecosystems.
At CES 2026, additional competitors signalled their
ambitions: Uber presented electric vehicles from Lucid that are scheduled to
enter robotaxi service around San Francisco later this year, powered by
autonomous software from Nuro. In Las Vegas itself, vehicles from Amazon-owned
Zoox — designed without steering wheels or pedals — are already operating on
public roads.
Against this backdrop, Nvidia’s strategy is not to become a
vehicle operator, but to position its AI stack as a foundational layer that can
be adopted by multiple manufacturers and service providers. The company expects
this platform approach to accelerate adoption across different markets and
vehicle segments.
Mercedes-Benz builds on Nvidia for US rollout
Mercedes-Benz is among the manufacturers placing early bets
on Nvidia’s autonomous driving ecosystem. At CES, the Germans highlighted their
MB.Drive system, which integrates Nvidia’s Drive AV full-stack software and the
Drive AGX accelerated computing platform.
The resulting system, branded MB.Drive Assist Pro, is
already available in China and is scheduled to launch in the United States
later this year. Operating at Level 2, it supports assisted driving from
parking space to destination while allowing drivers to intervene at any time
through a cooperative steering concept. The system processes data from around
30 sensors, including cameras, radar and ultrasonic units, and is positioned as
a stepping stone toward higher levels of automation.
With robotaxi services targeted for 2027 and consumer
vehicles to follow shortly after, Nvidia is signalling a clear shift: from
enabling autonomy in laboratories and pilot projects to embedding AI-driven
decision-making into everyday mobility. Whether this timeline holds will depend
not only on technology, but also on regulation, infrastructure and public
acceptance — yet the momentum behind AI-powered driving is clearly building.
