Autonomous Vehicle Companies: Robotaxis, Self-Driving AI and Valuations

After years of hype and disappointment, self-driving vehicles have become real. Fully driverless robotaxis now carry millions of paying passengers a year in several US cities, Chinese companies operate large robotaxi fleets, and autonomous trucks are running commercial routes. Private companies at the centre of this shift are among the most valuable in the world. This guide covers the autonomous vehicle companies in our database, the major public players, how the technology works and what still stands between autonomy and widespread profitability.

Each company in the table links to a full profile with sourced valuation, funding and investors.

Private autonomous vehicle companies in our database

The leaders

Waymo

Waymo, majority-owned by Alphabet, runs the world's leading fully driverless robotaxi service in cities including Phoenix, San Francisco, Los Angeles, Austin and Atlanta. It completed more than 14 million paid trips in 2025 and raised US$16 billion at a US$126 billion valuation in February 2026. Its approach combines lidar, cameras and radar with AI software developed over more than 15 years, and it expands city by city after extensive mapping and testing.

Applied Intuition

Applied Intuition doesn't run robotaxis; it sells simulation tools, autonomy software and vehicle operating systems to carmakers, truck makers and militaries. Valued at US$15 billion, it shows that the "picks and shovels" of autonomy can be as valuable as the vehicles themselves.

Wayve

London-based Wayve develops "end-to-end" AI driving software that learns to drive from data rather than relying on detailed maps and hand-written rules. It partners with carmakers, including Nissan, to bring its technology to consumer vehicles, and has tested robotaxi services with Uber. It was valued at about US$8.6 billion.

Waabi

Toronto's Waabi, founded by AI researcher Raquel Urtasun, focuses on autonomous trucking, using a generative AI simulator to train and validate its driving software, and has partnered with Volvo on driverless trucks.

Moove

Moove began by financing vehicles for ride-hailing drivers and now operates and maintains Waymo's robotaxi fleets in some cities, a sign that autonomy is creating new service businesses around fleets.

Public and big tech players

• Tesla: uses a camera-only approach trained on data from millions of customer cars, sells "Full Self-Driving (Supervised)" to owners and launched a robotaxi service in Austin in 2025.
• Zoox (Amazon): builds purpose-designed robotaxis without steering wheels and has launched service in Las Vegas.
• Baidu Apollo Go, Pony.ai and WeRide: Chinese companies operating large robotaxi fleets in China and expanding into the Middle East and Europe.
• Aurora: a public company running driverless trucks commercially in Texas.
• Mobileye: supplies driver assistance and autonomy systems to carmakers.

How self-driving technology works

An autonomous vehicle must perceive its surroundings, predict what other road users will do, plan a safe path and control the vehicle, many times per second. Most robotaxi companies use several sensor types: lidar, which measures distances with lasers; cameras, which capture colour and detail; and radar, which works well in bad weather. Software combines these inputs into a detailed picture of the world. Traditional approaches used separate modules for each task; newer "end-to-end" approaches train large neural networks to go directly from sensor data to driving decisions, similar to how large language models learn from data. Simulation lets companies test billions of virtual miles, including rare and dangerous situations that are hard to encounter in real driving.

Robotaxis versus personal cars versus trucks

Companies pursue different markets. Robotaxis, like Waymo's, remove the driver entirely and operate in defined areas, earning fares. Personal vehicle autonomy, like Tesla's and many carmakers' systems, assists or partly replaces human driving in cars people own, earning revenue from vehicle sales and software subscriptions. Autonomous trucking targets long highway routes, where driver shortages and costs are high and driving is more predictable. Each market has different technical challenges, regulations and business models.

The economics

Removing the driver eliminates the largest cost in ride-hailing, but autonomous vehicles are expensive: sensors, computers and engineering add significant cost per vehicle, and companies must pay for remote assistance, cleaning, charging, maintenance and insurance. Profitability depends on reducing hardware costs, increasing utilisation (how many hours each vehicle carries paying passengers), expanding to more cities efficiently and keeping safety high. Investors are betting that costs will fall as technology matures and scale grows, much as they have for batteries and solar panels.

Safety and regulation

Safety is the central question for public acceptance. Waymo has published data suggesting its vehicles are involved in far fewer injury-causing crashes per mile than human drivers in the same cities, while incidents involving other companies have led to permit suspensions and recalls. In the US, states regulate testing and deployment, while federal regulators oversee vehicle safety standards and investigate incidents. China, Europe, Japan and Gulf states have their own frameworks, with some actively encouraging robotaxi deployment.

Who invests in autonomy

Autonomy requires very large, long-term investment. Backers include technology giants (Alphabet, Amazon), carmakers (Toyota, Hyundai, Nissan, Volvo), chipmakers (Nvidia), ride-hailing platforms (Uber), sovereign funds and large growth investors such as Dragoneer, DST Global, Sequoia, Fidelity and T. Rowe Price. Many earlier autonomy startups failed or were acquired when funding dried up, including Argo AI and Cruise, which General Motors shut down in 2024, so investors now focus on companies with real deployments.

Questions for evaluating autonomy companies

• Are vehicles operating without safety drivers, and how many paid trips or miles do they complete?
• What is the cost per mile, and how fast is it falling?
• How is safety measured, and is the data independently reviewed?
• How quickly can the system expand to new cities or routes?
• Who are the commercial partners, and are contracts binding?

What to watch

Watch new city launches by Waymo and competitors, Tesla's robotaxi expansion, Chinese operators' international growth, autonomous trucking deployments, regulatory decisions and possible IPOs. Our guide to humanoid robot companies covers the related field of physical AI.

The role of AI breakthroughs

Advances in AI have accelerated autonomous driving. Large neural networks trained on vast amounts of driving data can handle a wider range of situations than earlier rule-based systems. Generative AI techniques let companies create realistic simulated scenarios to test rare events, such as a child running into the road or an unusual construction zone. Foundation models that combine vision and language can help vehicles understand complex scenes and instructions. These techniques connect autonomous vehicles to the broader physical AI movement, which also includes humanoid robots and other machines that act in the real world.

Autonomy beyond roads

The same technologies power autonomous systems in other domains: delivery robots on sidewalks, autonomous tractors in farms, mining trucks, warehouse vehicles, drones and military systems. Companies such as Applied Intuition sell software across several of these markets, and defense applications have become an important source of revenue for autonomy companies. Our guide to defense tech startups covers military autonomy in more detail.

Robotaxis and cities

Robotaxis raise questions for city governments about congestion, curb space, public transport and jobs for ride-hailing drivers. Some cities have welcomed driverless services as a way to improve mobility and road safety; others have raised concerns about vehicles blocking emergency responders or adding traffic. Labour groups worry about the impact on drivers' livelihoods. How cities and states regulate robotaxis, through permits, data reporting requirements and operating rules, will influence how quickly the technology spreads and which companies succeed.

Insurance and liability

When a driverless car crashes, responsibility shifts from human drivers towards the companies operating the vehicles. Insurers, regulators and courts are adapting to this change, and robotaxi operators carry significant insurance. Clear liability rules will be important for widespread adoption.

Public acceptance also depends on how companies communicate about incidents. Transparent reporting of crashes, disengagements and safety improvements builds trust, while delays or incomplete disclosure can lead regulators to suspend permits, as happened to Cruise in California in 2023.