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, 2026

Filed:

Aug. 01, 2019
Applicant:

Telefonaktiebolaget Lm Ericsson (Publ), Stockholm, SE;

Inventors:

Rafia Inam, Västerås, SE;

Alberto Hata, Campinas SP, BR;

Ahmad Ishtar Terra, Solna, SE;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05D 1/00 (2024.01); B60W 60/00 (2020.01);
U.S. Cl.
CPC ...
G05D 1/0088 (2013.01); B60W 60/0015 (2020.02); G05D 1/0214 (2013.01); B60W 2520/06 (2013.01); B60W 2520/10 (2013.01); B60W 2554/20 (2020.02); B60W 2554/40 (2020.02); B60W 2554/4042 (2020.02); B60W 2554/4044 (2020.02); B60W 2554/802 (2020.02);
Abstract

A method performed by a risk management node for autonomous devices. The risk management node may determine state parameters from a representation of an environment. The representation of the environment may include an object, an autonomous device, and a set of safety zones. The risk management node may determine a reward value based on evaluating a risk of a hazard with the object based on the determined state parameters and current location and speed of the autonomous device relative to a safety zone from the set of safety zones. The risk management node may determine a control parameter based on the determined reward value, and may initiate sending the control parameter to the autonomous device to control action of the autonomous device. The control parameter may be dynamically adapted to reduce the risk of hazard with the object based on reinforcement learning feedback from the reward value.


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