Uber is planning to turn its millions of drivers into a sensor grid to provide data for self-driving companies [1].

This move signals a shift in Uber's strategy to reintegrate autonomous vehicle technology into its network, leveraging its massive existing driver base to accelerate the development of self-driving cars.

Chief Technology Officer Praveen Neppalli Naga said the plan during an interview at TechCrunch’s StrictlyVC event in San Francisco on Thursday night [1]. Naga said the initiative as a natural extension of AV Labs, a program the company announced in late January [1].

By utilizing driver data, Uber aims to create a comprehensive data set for autonomous vehicle developers. This approach allows the company to gather real-world driving data at a scale that few other companies can match.

Uber has remained on the sidelines of the robotaxi market for six years [2]. The company is now making a clear push to deploy its own robotaxis again, using deal structures designed to limit risk [2].

Naga said the plan is an extension of the nascent program launched earlier this month. The integration of human drivers as a sensor grid represents a transition from Uber's previous approach to autonomous driving.

According to reports, Uber is exploring options to operate its own robotaxi fleet, potentially utilizing vehicles from manufacturers like Rivian [2]. This shift suggests a move toward a partnership-based model rather than developing proprietary self-driving technology from scratch.

The program's scale is potentially enormous, given the millions of drivers currently active in the Uber network. By turning these drivers into a sensor grid, Uber is creating a value proposition for self-driving companies that relies on the data-gathering capabilities of its existing infrastructure.

“Uber is planning to turn its millions of drivers into a sensor grid to provide data for self-driving companies.”

Uber's transition to a sensor grid model suggests a move toward becoming a data provider for the autonomous vehicle industry. By leveraging its existing driver network, Uber is reducing the risk of the costly and expensive R&D of proprietary hardware. Instead, it is positioning itself as the essential infrastructure for any self-driving company that needs real-world, edge-case data to achieve full autonomy.