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. 21, 2025

Filed:

Jul. 07, 2022
Applicant:

GM Cruise Holdings Llc, San Francisco, CA (US);

Inventors:

Livia Johanna, San Francisco, CA (US);

Hailun Zhou, San Francisco, CA (US);

Theresa Foy, San Francisco, CA (US);

Assignee:

GM Cruise Holdings LLC, San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04M 3/523 (2006.01); B60W 40/08 (2012.01); B60W 50/00 (2006.01); B60W 60/00 (2020.01); G06V 20/58 (2022.01);
U.S. Cl.
CPC ...
H04M 3/5233 (2013.01); B60W 40/08 (2013.01); B60W 50/00 (2013.01); B60W 60/0013 (2020.02); B60W 60/00253 (2020.02); G06V 20/58 (2022.01); B60W 2050/0028 (2013.01); B60W 2050/0083 (2013.01); B60W 2420/403 (2013.01); B60W 2556/10 (2020.02);
Abstract

Assistance can be provided to users of AVs based on user sentiments. A system may receive a request for assistance from a user of an AV (e.g., a passenger of the AV). The system may also receive sensor data that is captured by a sensor suite of the AV from detecting the user, the AV, or another object. The system determines a sentiment of the user based on the sensor data. The system may input the sensor data into a machine learning model and the model outputs information indicating the user's sentiment. The system can determine who, when, or how to service the user's request based on the user's sentiment. The system may assign the user's request to an agent who can provide the assistance. The system can further provide guidance (e.g., suggested content of a conversation with the user) to the agent based on the user's sentiment.


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