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. 29, 2025

Filed:

Dec. 28, 2021
Applicant:

Ford Global Technologies, Llc, Dearborn, MI (US);

Inventors:

John Lepird, Pittsburgh, PA (US);

Pragati Satpute, Canton, MI (US);

Ramadev Burigsay Hukkeri, Pittsburgh, PA (US);

Assignee:

Ford Global Technologies, LLC, Dearborn, MI (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
B60W 30/095 (2012.01); B60W 30/09 (2012.01); B60W 40/04 (2006.01); B60W 50/00 (2006.01); B60W 60/00 (2020.01); G06N 3/02 (2006.01); G06N 3/0442 (2023.01); G06N 3/045 (2023.01); G06N 3/09 (2023.01); G06N 5/01 (2023.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
B60W 30/0956 (2013.01); B60W 30/09 (2013.01); B60W 40/04 (2013.01); B60W 50/0097 (2013.01); B60W 60/0011 (2020.02); B60W 60/00274 (2020.02); G06N 3/02 (2013.01); B60W 2554/4041 (2020.02); B60W 2556/10 (2020.02);
Abstract

Disclosed herein are system, method, and computer program product aspects for enabling an autonomous vehicle (AV) to react to objects posing a risk to the AV. The system can monitor an object within a vicinity of the AV. A plurality of trajectories predicting paths the object will take can be generated, the plurality of trajectories being based on a plurality of inputs indicating current and past characteristics of the object. Using a learned model, a forecasted position of the object at an instance in time can be generated. An error value representing how accurate the forecasted position is versus an observed position of the object can be stored. Error values can be accumulated over a period of time. A risk factor can be assigned for the object based on the accumulated error values. A maneuver for the AV can be performed based on the risk factor.


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