Uber Technologies, Inc.

Andrew Heine

William Payne Ross

Benjamin Kroop

A system can analyze a live sensor view of a self-driving vehicle (SDV) in accordance with a safety threshold to detect objects of interest along a route and classify each detected object of interest. When the safety threshold is not met, the system can transmit a teleassistance inquiry using LIDAR data to a backend computing system. When a certainty threshold is not met for an object of interest, the system can transmit a different teleassistance inquiry using image data to the backend computing system.

Teleassistance data prioritization for self-driving vehicles

A self-driving vehicle can operate by analyzing a live sensor view to autonomously operate acceleration, braking, and steering systems of the SDV along a current route. Based on a detected anomaly associated with the live sensor view, the SDV can transmit a teleassistance inquiry to a backend transport system in accordance with a data prioritization scheme. The SDV can receive a resolution response from the backend transport system based on the teleassistance inquiry, and proceed in accordance with the resolution response.

A self-driving vehicle (SDV) can analyze a live sensor view to autonomously operate acceleration, braking, and steering systems of the SDV along a current route. The SDV can identify an indeterminate object in the live sensor view, and encoding sensor data identifying the indeterminate object for transmission to a backend transport system over one or more networks. The SDV may then receive a resolution response from the backend transport system to resolve the indeterminate object, and cause the SDV to proceed in accordance with the resolution response.

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Pittsburgh, PA, United States of America

Andrew Heine