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:
Jan. 31, 2023

Filed:

Aug. 29, 2019
Applicant:

Zoox, Inc., Foster City, CA (US);

Inventors:

Timothy Caldwell, Mountain View, CA (US);

Jefferson Bradfield Packer, San Francisco, CA (US);

William Anthony Silva, San Francisco, CA (US);

Rick Zhang, San Mateo, CA (US);

Gowtham Garimella, Burlingame, CA (US);

Assignee:

Zoox, Inc., Foster City, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B60W 50/06 (2006.01); B60W 50/04 (2006.01); B60W 50/00 (2006.01); G05B 13/02 (2006.01); G06N 3/08 (2006.01); G05B 13/04 (2006.01);
U.S. Cl.
CPC ...
B60W 50/06 (2013.01); B60W 50/00 (2013.01); B60W 50/045 (2013.01); G05B 13/027 (2013.01); G05B 13/042 (2013.01); G06N 3/088 (2013.01); B60W 2050/0075 (2013.01);
Abstract

Techniques for generating simulations for evaluating a performance of a controller of an autonomous vehicle are described. A computing system may evaluate the performance of the controller to navigate the simulation and respond to actions of one or more objects (e.g., other vehicles, bicyclists, pedestrians, etc.) in a simulation. Actions of the objects in the simulation may be controlled by the computing system (e.g., by an artificial intelligence) and/or one or more users inputting object controls, such as via a user interface. The computing system may calculate performance metrics associated with the actions performed by the vehicle in the simulation as directed by the autonomous controller. The computing system may utilize the performance metrics to verify parameters of the autonomous controller (e.g., validate the autonomous controller) and/or to train the autonomous controller utilizing machine learning techniques to bias toward preferred actions.


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