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. 04, 2023

Filed:

Jul. 24, 2020
Applicant:

Bayerische Motoren Werke Aktiengesellschaft, Munich, DE;

Inventors:

Jilei Tian, Chicago, IL (US);

Yang Cao, Chicago, IL (US);

Sascha Hamzehi, Dachau, DE;

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G01C 21/34 (2006.01); G06N 20/00 (2019.01); G06F 18/21 (2023.01);
U.S. Cl.
CPC ...
G01C 21/343 (2013.01); G01C 21/3446 (2013.01); G06F 18/217 (2023.01); G06N 20/00 (2019.01);
Abstract

Examples relate to systems, method and systems, methods and computer programs for efficiently determining an order of driving destinations and for training a machine-learning model using distance-based input data. A system for determining an order of a plurality of driving destinations is configured to obtain information on a distance between the plurality of driving destinations, the distance being defined for a plurality of routes between the plurality of driving destinations, with the routes being defined separately in both directions between each combination of driving destinations of the plurality of driving destinations within the information on the distance. The system is configured to provide the information on the distance between the plurality of driving destinations as input to a machine-learning model, the machine-learning model being trained to output information on an order of the plurality of routes based on the information on the distance provided at the input of the machine-learning model. The system is configured to determine the information on the order of the plurality of driving destinations based on the information on the order of the plurality of routes.


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