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

Uber has a long-term ambition that goes far beyond transporting passengers: The company eventually wants to equip its drivers’ cars with sensors to ingest real-world data for autonomous vehicle (AV) companies — and potentially other companies that train AI models in real-world scenarios.

Praveen Neppalli Naga, Uber’s chief technology officer, revealed the plan in an interview with TechCrunch’s StrictlyVC event in San Francisco on Thursday night, describing it as a natural extension of a nascent program the company announced in late January called AV Labs.

“That’s the direction we want to go eventually,” Naga said of equipping the vehicles with human drivers. “But first we have to understand the sensor kits and how they all work. There are some regulations — we have 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 network of drivers. 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 bring to the AV industry would be smaller than what any individual AV company could assemble on its own.

The idea driving the program, Naga said, is that the limiting factor for AV development is no longer the underlying technology. “The bottleneck is the data,” he said. “[Companies like Waymo] you have to browse and collect the data, collect different scenarios. Maybe you can say: in San Francisco, “At this school intersection, I want some data at this time of day so I can train my models.” The problem for all these companies is access to this data, because they don’t have the capital to develop the cars and collect all this information.”

Becoming the data layer for the entire AV ecosystem is a pretty smart play, especially when you consider that Uber years ago abandoned its ambitions to build self-driving cars (a move that co-founder Travis Kalanick has publicly lamented as a big mistake). Indeed, many industry watchers have wondered whether, without its own self-driving cars, Uber could one day become irrelevant as AVs increasingly spring 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 sensor-tagged data that partner companies can search and use to train their models. Partners, which Uber plans to do more aggressively invest directlythey can also use the system to run their trained models in “shadow mode” against real Uber trips, simulating how an AV would perform without actually putting it on the road.

“Our goal is not to make money from this data,” Naga said. “We want to democratize it.”

Given the obvious commercial value of what Uber is building, that position may not last long. The company has already made equity investments in several AV players, and its ability to offer proprietary training data at scale could give it significant leverage in a sector that currently depends on Uber’s marketplace to reach customers.