Uber is exploring a plan to equip driver vehicles with sensors to collect real-world data, aiming to expand its role as a data provider for autonomous vehicle development and AI training.
Strategy Extends From AV Labs Program
Chief technology officer Praveen Neppalli Naga outlined the initiative during a discussion at the StrictlyVC event in San Francisco. He said the approach builds on Uber’s AV Labs program, introduced earlier this year, which currently uses a small fleet of company-operated vehicles equipped with sensors.
Naga said expanding the program to include driver vehicles would require further understanding of sensor systems and regulatory clarity across different jurisdictions.
Large Driver Network Offers Potential Scale Advantage
Uber operates a global network of millions of drivers. If a portion of those vehicles were outfitted with sensors, they could serve as distributed data collection points, significantly increasing the volume and diversity of real-world driving data available for autonomous vehicle systems.
Data Collection Identified As Key Industry Bottleneck
Naga said the primary limitation in autonomous vehicle development is no longer core technology but access to data. He noted that companies such as Waymo must deploy vehicles to gather specific driving scenarios, which can be resource-intensive.
He said Uber’s network could provide targeted datasets, such as traffic conditions at specific locations and times, to support model training.
AV Cloud Platform Supports Partner Ecosystem
Uber is developing what it describes as an “AV cloud,” a system that stores labeled sensor data for use by partner companies. The platform allows partners to query datasets and test their models in simulated environments using real trip data, a process referred to as shadow mode.
The company currently works with 25 autonomous vehicle partners, including Wayve, and has made equity investments in several of them.
Positioning Focuses On Data Access Rather Than Direct Monetization
Naga said Uber’s stated goal is to make data broadly accessible to partners, though the scale of its dataset could provide strategic advantages as the autonomous vehicle sector develops.
The initiative reflects Uber’s shift from earlier efforts to build its own autonomous vehicles toward supporting external developers through its platform and infrastructure.
Featured image credits: Flickr
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