Uber wants to turn its millions of drivers into a sensor grid for self-driving companies

Uber has a long-term ambition that goes well beyond ferrying passengers: The company wants to eventually equip its human drivers’ cars with sensors to ingest real-world data for autonomous vehicle (AV) companies – and possibly other companies that train AI models on scenarios in the physical world.

Praveen Neppalli Naga, Uber’s chief technology officer, revealed the plan in an interview at JS’s Strictly VC event in San Francisco on Thursday evening, describing it as a natural extension of an emerging program the company announced in late January called AV Labs.

“That’s the direction we ultimately want to take,” Naga said of equipping vehicles with human drivers. “But first we need to understand the sensor kits and how they all work. There are some rules – we need to make sure every state has [clarity on] what sensors mean and what sharing them means.”

For now, AV Labs relies on a small, dedicated fleet of sensor-equipped cars that Uber operates itself, separate from its driver network. But the ambition is clearly much greater. Uber has millions of drivers worldwide, and if even a fraction of those cars could be turned into rolling data collection platforms, the scale of what Uber could offer the AV industry would dwarf what an individual AV company could put together on its own.

The insight driving the program, Naga says, is that the limiting factor for AV development is no longer the underlying technology. “The bottleneck is the data,” he says. “[Companies like Waymo] have to go around and collect the data, collect different scenarios. You might say, in San Francisco, “At this intersection of schools, I want to have some data at this time so I can train my models.” The problem for all these companies is access to that data, because they don’t have the capital to deploy the cars and collect all this information.”

Becoming the data layer for the entire AV ecosystem is a pretty smart move, especially considering that Uber abandoned its own ambitions to build self-driving cars years ago (a move that co-founder Travis Kalanick has publicly lamented as a big mistake). Indeed, many industry observers have wondered whether Uber, without its own self-driving cars, could one day become irrelevant as AVs continue to pop up around the world.

The company currently has partnerships with 25 AV companies – including Wayve, which operates in London – and is building what Naga described as an “AV cloud”: a library of labeled sensor data that partner companies can query and use to train their models. Partners, where Uber plans to be more aggressive invest directly in itcan also use the system to run their trained models in ‘shadow mode’ against real Uber rides, simulating how an AV would have performed without actually putting one on the road.

“Our goal is not to monetize this data,” says Naga. “We want to democratize it.”

Given the clear commercial value of what Uber is building, that positioning may not last long. The company has already made equity investments in numerous AV players, and its ability to offer its own training data at scale could give it significant leverage in an industry that currently relies on Uber’s ride-hailing market to reach customers.