UBER PLANS TO USE DRIVERS AS SENSOR NETWORK FOR SELF-DRIVING

Uber intends to transform its driver network into a distributed sensor grid to support self-driving technology companies. The move represents a shift in how the ride-hailing company approaches autonomous vehicle development following years of struggles with its own self-driving division. Neppalli Naga disclosed the plan during a presentation at TechCrunch's StrictlyVC conference in San Francisco Thursday. He framed the initiative as a natural progression of AV Labs, Uber's recently launched program focused on autonomous vehicle advancement. The approach would essentially turn Uber's fleet of millions of drivers into mobile data collectors. Vehicles in the network would gather information through their existing sensors—cameras, lidar, and radar systems—providing real-world driving data across numerous geographies and conditions. This data collection could benefit multiple self-driving companies, creating a valuable resource for training and validating autonomous systems. The strategy addresses a significant challenge in autonomous vehicle development: obtaining diverse, real-world training data at scale. Rather than investing heavily in proprietary sensor networks or relying on limited testing programs, Uber could monetize its existing infrastructure and driver base. This pivot marks a notable change from Uber's previous autonomous vehicle efforts. The company shuttered its self-driving division in 2020 and sold its autonomous truck unit Advanced Technologies Group to Aurora Innovation. The new approach suggests Uber is positioning itself as a data provider and platform facilitator rather than a direct competitor in autonomous vehicle manufacturing. The program could generate additional revenue streams for Uber while reducing capital expenditure on autonomous technology development. For autonomous vehicle companies, access to Uber's driver data would provide unprecedented scale and diversity for training algorithms. Details regarding data sharing agreements, compensation structures, and privacy safeguards have not been disclosed. The initiative is expected to expand as AV Labs develops further.