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:
Aug. 11, 2026

Filed:

Oct. 25, 2024
Applicant:

Toyota Research Institute, Inc., Los Altos, CA (US);

Inventors:

Andrew Michael Silva, Cambridge, MA (US);

Emily Sarah Sumner, Cambridge, MA (US);

Jonathan A. Decastro, Arlington, MA (US);

Deepak Edakkattil Gopinath, Washington, DC (US);

Thomas M. Balch, Damariscotta, ME (US);

Xiongyi Cui, Somerville, MA (US);

Guy Rosman, Cambridge, MA (US);

Assignees:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
B60W 60/00 (2020.01); B60Q 1/14 (2006.01); B60Q 1/34 (2006.01); B60Q 5/00 (2006.01); B60W 10/18 (2012.01); B60W 10/20 (2006.01); B60W 10/30 (2006.01); B60W 50/00 (2006.01); B60W 50/10 (2012.01); B60W 50/14 (2020.01);
U.S. Cl.
CPC ...
B60W 60/001 (2020.02); B60Q 1/14 (2013.01); B60Q 1/346 (2013.01); B60Q 5/005 (2013.01); B60W 10/18 (2013.01); B60W 10/20 (2013.01); B60W 10/30 (2013.01); B60W 50/0097 (2013.01); B60W 50/10 (2013.01); B60W 50/14 (2013.01); B60W 2540/21 (2020.02); B60W 2540/229 (2020.02); B60W 2540/30 (2013.01);
Abstract

Systems and methods for assisting a driver using a foundation model in a shared-autonomy driving mode of a vehicle are disclosed herein. One embodiment of a shared-autonomy assistance subsystem processes, in a vehicle operating in a shared-autonomy driving mode, inputs including vehicle state information, external-road-agent state information, vehicle environmental sensor data, and map data using one or more encoder neural networks that have been trained to extract features for a large language model (LLM). The subsystem inputs the extracted features to the LLM. The subsystem predicts, using the LLM, an objective of a driver of the vehicle. The subsystem then executes, based on an output from the LLM, one or more actions to assist the driver in meeting the predicted objective. The one or more actions include controlling, at least in part, operation of the vehicle.


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