The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 10, 2018

Filed:

Oct. 24, 2017
Applicant:

Uber Technologies, Inc., San Francisco, CA (US);

Inventors:

Colin Jeffrey Green, Pittsburgh, PA (US);

Wei Liu, Pittsburgh, PA (US);

David McAllister Bradley, Pittsburgh, PA (US);

Vijay Subramanian, Pittsburgh, PA (US);

Assignee:

Uber Technologies, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01C 22/00 (2006.01); G05D 1/02 (2006.01); G05D 1/00 (2006.01); B60W 30/095 (2012.01); B60W 30/18 (2012.01); G08G 1/16 (2006.01);
U.S. Cl.
CPC ...
G05D 1/0221 (2013.01); B60W 30/0953 (2013.01); B60W 30/18109 (2013.01); B60W 30/18154 (2013.01); G05D 1/0088 (2013.01); G05D 1/0223 (2013.01); G08G 1/166 (2013.01); B60W 2550/22 (2013.01); G05D 2201/0213 (2013.01);
Abstract

The present disclosure provides autonomous vehicle systems and methods that include or otherwise leverage a machine-learned yield model. In particular, the machine-learned yield model can be trained or otherwise configured to receive and process feature data descriptive of objects perceived by the autonomous vehicle and/or the surrounding environment and, in response to receipt of the feature data, provide yield decisions for the autonomous vehicle relative to the objects. For example, a yield decision for a first object can describe a yield behavior for the autonomous vehicle relative to the first object (e.g., yield to the first object or do not yield to the first object). Example objects include traffic signals, additional vehicles, or other objects. The motion of the autonomous vehicle can be controlled in accordance with the yield decisions provided by the machine-learned yield model.


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