Uber Technologies plans to transform its millions of drivers into a data collection network to support autonomous vehicle development, the company's chief technology officer announced Thursday.

Praveen Neppalli Naga revealed the initiative during an interview at TechCrunch's StrictlyVC event in San Francisco, describing it as an expansion of the company's AV Labs program launched in January. The program would utilize Uber's extensive driver fleet to gather real-world driving data that could benefit self-driving technology companies.

The proposal represents a significant shift in how ride-sharing companies might contribute to autonomous vehicle development. By equipping drivers with sensors or data collection tools, Uber could create one of the largest real-world driving datasets available to the industry.

Uber's driver network spans millions of vehicles across hundreds of cities globally, potentially offering unprecedented geographic coverage for autonomous vehicle training data. The company has not disclosed specific technical details about how the sensor grid would operate or which self-driving companies might access the collected information.

The announcement comes as the autonomous vehicle industry continues seeking diverse data sources to improve self-driving algorithms. Real-world driving scenarios captured through Uber's network could provide valuable insights into traffic patterns, road conditions, and driver behavior across different markets and conditions.