A new strategy is emerging at Uber as it looks to play a larger role in the autonomous vehicle ecosystem by leveraging its global driver network.
The company is exploring a plan to equip drivers’ vehicles with sensor kits to collect real-world data for autonomous vehicle (AV) companies and other AI applications. The idea was shared by Praveen Neppalli Naga, Uber’s chief technology officer, who described it as a long-term direction.
“That is the direction we want to go eventually,” Naga said. “But first we need to get the understanding of the sensor kits and how they all work. There are some regulations — we have to make sure every state has [clarity on] what sensors mean, and what sharing it means.”
Currently, Uber is testing this concept through its AV Labs program, which uses a small fleet of company-operated, sensor-equipped vehicles. However, the long-term vision is far more ambitious. With millions of drivers worldwide, even partial adoption could create one of the largest real-world data networks for AV development.
According to Naga, the main challenge in autonomous driving today is not technology but access to data. “The bottleneck is data,” he said. “[Companies like Waymo] need to go around and collect the data, collect different scenarios.”
Uber is positioning itself as a data infrastructure provider for the AV ecosystem. The company is building what it calls an “AV cloud”, a structured library of sensor data that partners can use to train their models. It currently collaborates with 25 AV companies, including Wayve.
Partners can also test their systems in “shadow mode”, where models are run against real Uber trips without deploying actual self-driving vehicles.
“Our goal is not to make money out of this data,” Naga said. “We want to democratize it.”
This strategy marks a shift from Uber’s earlier efforts to build its own autonomous vehicles. By focusing on data, the company aims to stay relevant in a future where self-driving technology becomes widespread.
At the same time, its ability to provide large-scale, real-world data could give it significant influence in a sector that depends on both data and access to customers.
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