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:
May. 28, 2024

Filed:

Jan. 17, 2023
Applicant:

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

Inventors:

Antony Joseph, San Francisco, CA (US);

Geoffrey Louis Chi-Johnston, San Francisco, CA (US);

Vishal Suresh Vaingankar, Kensington, CA (US);

Laura Athena Freeman, San Francisco, CA (US);

Assignee:

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

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2006.01); G01C 21/20 (2006.01); G01C 21/34 (2006.01); G01C 21/36 (2006.01);
U.S. Cl.
CPC ...
G05D 1/0214 (2013.01); G01C 21/20 (2013.01); G01C 21/3484 (2013.01); G01C 21/3691 (2013.01); G05D 1/0011 (2013.01); G05D 1/0061 (2013.01);
Abstract

Various technologies described herein pertain to routing autonomous vehicles based upon spatiotemporal factors. A computing system receives an origin location and a destination location of an autonomous vehicle. The computing system identifies a route for the autonomous vehicle to follow from the origin location to the destination location based upon output of a spatiotemporal statistical model. The spatiotemporal statistical model is generated based upon historical data from autonomous vehicles when the autonomous vehicles undergo operation-influencing events. The spatiotemporal statistical model takes, as input, a location, a time, and a direction of travel of the autonomous vehicle. The spatiotemporal statistical model outputs a score that is indicative of a likelihood that the autonomous vehicle will undergo an operation-influencing event due to the autonomous vehicle encountering a spatiotemporal factor along a candidate route. The autonomous vehicle then follows the route from the origin location to the destination location.


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