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

Uber has a long-term ambition that goes well beyond transporting passengers: The company eventually wants to outfit its human drivers’ cars with sensors to soak up 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 at 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 vehicles with human drivers. “But first we need to get an understanding of the sensor sets and how they all work. There are some rules – we need to make sure that every state has [clarity on] what sensors mean and what sharing means.”

For now, AV Labs relies on a small, dedicated fleet of sensor-equipped cars that Uber itself operates, separate from its driver network. But the ambition is clearly much greater. Uber has millions of drivers globally, 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 any individual AV company could muster on its own.

The insight driving the program, Naga said, is that the limiting factor for AV development is no longer the underlying technology. “The bottleneck is data,” he said. “[Companies like Waymo] have to go around and collect data, collect different scenarios. You might say: in San Francisco, ‘In 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 that data because they don’t have the capital to install the cars and collect all that information.”

Becoming the data layer for the entire AV ecosystem is a pretty smart play, especially given 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, might one day be rendered irrelevant as AVs increasingly 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 that Uber plans to invest more aggressively in directly can 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,” Naga said. “We want to democratize it.”

Given the obvious commercial value of what Uber is building, this positioning 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 over a sector that currently depends on Uber’s ride-hailing marketplace to reach customers.