Uber wants to turn its drivers into a sensor grid for self-driving companies
Uber aims to leverage its global network of millions of drivers as a data collection system for autonomous vehicle companies by equipping their vehicles with sensors. The initiative, part of a program called AV Labs, seeks to address the data bottleneck currently limiting AV development. While currently using a small dedicated fleet, Uber's long-term vision is to create a scalable, real-world data platform for AI and AV training.
- ▪Uber's CTO Praveen Neppalli Naga revealed plans to equip human drivers' cars with sensors to collect data for autonomous vehicle companies.
- ▪The AV Labs program currently uses a small fleet of Uber-owned sensor-equipped vehicles, separate from its driver network.
- ▪Uber has partnerships with 25 AV companies and is building an 'AV cloud' of labeled sensor data for model training and simulation.
- ▪Naga stated that data collection is the main bottleneck in AV development, not the underlying technology.
- ▪Uber plans to democratize access to this data, though it has already made equity investments in several AV companies.
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Uber has a long-term ambition that goes well beyond shuttling 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 training AI models on physical-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 is the direction we want to go eventually,” Naga said of equipping human drivers’ vehicles. “But first we need to get the understanding of the sensor kits and how they all work.
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