Uber Technologies, Inc.

Sean Shanshi Chen

Samann Ghorbanian-Matloob

Michael Guanran Huang

Brent Justin Goldman

Patrick Greaney Willett

Eli Schleifer

Arvind Srinivasan

Shelley Bower

Systems and methods for controlling autonomous vehicles are provided. Assisted autonomy tasks facilitated by operators for a plurality of autonomous vehicles can be tracked in order to generate operator attributes for each of a plurality of operators. The attributes for an operator can be based on tracking one or more respective assisted autonomy tasks facilitated by the operator. The operator attributes can be used to facilitate enhanced remote operations for autonomous vehicles. For example, request parameters can be obtained in response to a request for remote assistance associated with an autonomous vehicle. An operator can be selected to assist with autonomy tasks for the autonomous vehicle based at least in part on the operator attributes for the operator and the request parameters associated with the request. Remote assistance for the first autonomous vehicle can be initiated, facilitated by the first operator in response to the request for remote assistance.

Context-based remote autonomous vehicle assistance

Disclosed are autonomous vehicles that may autonomously navigate at least a portion of a route defined by a service request allocator. The autonomous vehicle may, at a certain portion of the route, request remote assistance. In response to the request, an operator may provide input to a console that indicates control positions for one or more vehicle controls such as steering position, brake position, and/or accelerator position. A command is sent to the autonomous vehicle indicating how the vehicle should proceed along the route. When the vehicle reaches a location where remote assistance is no longer required, the autonomous vehicle is released from manual control and may then continue executing the route under autonomous control.

Operator assistance for autonomous vehicles

The present disclosure is directed to using anomaly data detected in traffic data to efficiently initiate remote assistance sessions. In particular, a computing system can receive, from a computing device associated with a human-driven vehicle, travel data for the human-driven vehicle. The computer system can identify a navigation anomaly associated with the human-driven vehicle based on the travel data. The computer system can generate, based on the identified navigation anomaly, an anomaly entry for storage in an anomaly database, the anomaly entry comprising geofence data describing a geographic area associated with the navigation anomaly. The computer system can determine, based on location data received from an autonomous vehicle and the geofence data, that the autonomous vehicle is entering the geographic area associated with the navigation anomaly. The computer system can initiate a remote assistance session with the autonomous vehicle.

System and methods for automatic generation of remote assistance sessions based on anomaly data collected from human-driven vehicle

Systems and methods for vehicle motion control with interactive object annotation are provided. A method can include obtaining data indicative of a plurality of objects within a surrounding environment of the autonomous vehicle. For example, the plurality of objects can include at least at one problem object encountered by the autonomous vehicle while navigating a planned route. The method can include determining a group of objects of the plurality of objects. For example, the group of objects can include the problem object and one or more other objects in proximity to the problem object. The method can include determining a classification update to be applied to the group of objects. The method can include applying the classification update to the group of objects. The method can include providing data indicative of the classification update for the group of objects to the autonomous vehicle for use in motion planning.

Systems and methods for vehicle motion control with interactive object annotation

The present disclosure is directed to a system for generating customized command toolboxes for remote operators in a service system that includes autonomous vehicles. The system receives a request for remote assistance from an autonomous vehicle. The system determines, from a local storage location, vehicle data associated with the autonomous vehicle. The system selects a subset of remote assistance actions from a predetermined set of remote assistance actions. The system displays, in a remote assistance user interface, one or more user interface elements indicative of the subset of remote assistance actions. The system determines one or more remote assistance actions from the subset of remote assistance actions based at least in part on a user input associated with the one or more user interface elements. The system transmits one or more control signals associated with the one or more remote assistance actions.

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San Francisco, CA, United States of America

Sean Shanshi Chen