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:
Oct. 22, 2019

Filed:

Feb. 15, 2017
Applicant:

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

Inventors:

Zhen Jiang, Mountain View, CA (US);

Yan Fu, Bloomfield Hills, MI (US);

Yuzhou Li, Palo Alto, CA (US);

Assignee:

FORD GLOBAL TECHNOLOGIES, LLC, Dearborn, MI (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2006.01); B60W 30/095 (2012.01); B60W 10/18 (2012.01); B60W 10/20 (2006.01); B60W 30/09 (2012.01); G05B 13/04 (2006.01); G05D 1/02 (2006.01);
U.S. Cl.
CPC ...
B60W 30/0953 (2013.01); B60W 10/18 (2013.01); B60W 10/20 (2013.01); B60W 30/09 (2013.01); G05B 13/048 (2013.01); G05D 1/0088 (2013.01); G05D 1/0231 (2013.01); G05D 1/0255 (2013.01); G05D 1/0257 (2013.01); G05D 2201/0213 (2013.01);
Abstract

A computer system receives data sets for a driving maneuver at a location, such as data regarding a state of a vehicle, an external environment indicated by external sensors, and user feedback regarding the driving maneuver. Data sets may be collected from users having various demographic and behavioral attributes. Users may be selected using design of experiment (DOE) algorithms to cover a wide range of possible combinations. A stochastic response surface model (SRSM) is generated that relates sensor data (vehicle state and environmental) to user feedback regarding safety and comfort. The SRSM may be generated using Gaussian process regression (GPR) in order to model uncertainty. The SRSM is then used to generate a control model using an optimization under uncertainty (OUU) algorithm.


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