Uber said it has launched AV Labs, a dedicated team designed to accelerate autonomous vehicle development by leveraging data collected from its global ride-hailing network.
The initiative focuses on what Uber describes as a central bottleneck in autonomous driving: access to large volumes of diverse, real-world driving data. By analysing trips taken across its platform, the company aims to help autonomous vehicle developers capture rare and complex driving scenarios that are difficult and expensive to generate through traditional testing or simulation alone.
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Danny Guo, Uber’s vice president of engineering and science, said modern autonomous systems increasingly rely on machine learning models trained on real-world conditions. “At-scale access to long-tail driving scenarios is critical for improving perception, prediction and planning,” Guo said, outlining the rationale behind the formation of AV Labs.
Uber processes millions of trips each day across cities worldwide, spanning dense urban cores, suburban roads, airports and commercial districts, and occurring under a wide range of traffic, weather and lighting conditions. The company said this breadth of operational data enables the identification of edge cases that are essential for improving autonomous system robustness.
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AV Labs will bring together engineers and researchers specializing in machine learning, computer vision, data systems and infrastructure. According to Uber, the team’s work will span data mining, simulation, validation and system-level improvements, with a focus on perception systems, motion prediction models and real-time planning algorithms.
Uber said the group will support its existing autonomous vehicle partners rather than developing its own self-driving cars. The company currently collaborates with autonomous technology providers including Waymo and has announced partnerships with other developers as part of its strategy to act as a platform and infrastructure provider within the AV ecosystem.
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The company added that AV Labs is actively recruiting technical talent to expand its capabilities. Uber said the initiative reflects its view that data infrastructure and ecosystem partnerships, rather than vertically integrated vehicle development, will play a key role in the next phase of autonomous mobility.