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. 28, 2020

Filed:

Dec. 22, 2017
Applicant:

Lyft, Inc., San Francisco, CA (US);

Inventors:

Farzad Cyrus Foroughi Abari, San Bruno, CA (US);

Aaron Jacob Levine Friedman, San Francisco, CA (US);

John Houston, San Francisco, CA (US);

Adam Hart Reis, San Francisco, CA (US);

Alexander Thomas Starns, Menlo Park, CA (US);

Assignee:

Lyft, Inc., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01C 22/00 (2006.01); G05D 1/00 (2006.01); G07C 5/08 (2006.01); G06N 5/04 (2006.01); G07C 5/00 (2006.01); G05D 1/02 (2020.01); G06N 20/00 (2019.01); G06Q 50/30 (2012.01); G06Q 10/00 (2012.01); G06Q 10/06 (2012.01); G06Q 10/02 (2012.01);
U.S. Cl.
CPC ...
G07C 5/0808 (2013.01); G05D 1/0088 (2013.01); G05D 1/0291 (2013.01); G06N 5/04 (2013.01); G06N 20/00 (2019.01); G06Q 10/02 (2013.01); G06Q 10/063 (2013.01); G06Q 10/20 (2013.01); G06Q 50/30 (2013.01); G07C 5/006 (2013.01);
Abstract

In particular embodiments, a computing system may generate a prediction of requests for autonomous vehicles in a fleet of collectively managed autonomous vehicles based on a current condition and a future event, the prediction including a predicted request level and a predicted duration of the request level. The system may receive status information from fleet vehicles and identify a vehicle in need of service. The system may receive status information from service centers and identify a service center to service the vehicle. The system may determine a time at which to service the vehicle at the identified service center based on the generated prediction of requests, schedule the vehicle for service at the identified service center at the determined time, and instruct the vehicle to drive to the service center to be serviced at the determined time. In particular embodiments, the prediction of requests may be generated using machine learning.


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