US 2024/0203173 A1Published application

System and/or method for predicting user action in connection with a vehicle user interface using machine learning

AssigneeMercedes-Benz Group AG

InventorsYahya Sowti Khiabani, Chieh Hsu, Charles Furrer, Dat Nguyen

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Abstract

Disclosed are a system, method and system to predict an individual's action in connection with a vehicle user interface using machine learning. One or more models may be developed based, at least in part, on observations of past actions by the individual among the plurality of target actions by the individual. Extracted features of a current context may be applied to the developed one or more models to predict a subsequent action among the target actions by the individual.

Claims20

Dependent claims

A system to be disposed in a vehicle, the system comprising:

one or more memory devices;
and
one or more processors coupled to the memory devices to:
determine features indicative of a context in which the vehicle is currently operating and/or a context in which a driver and/or a passenger is/are currently operating the vehicle;
generate a prediction of a future vehicle user interface action, from among a plurality of available vehicle user interface actions, wherein the prediction to be generated based, at least in part, on:
the features indicative of the context in which the vehicle is currently operating or the context in which the driver and/or the passenger is/are currently operating the vehicle;
and
user action context parameters relating:
(i) at least one past vehicle user interface action requested by at least one past driver and/or past passenger of an associated vehicle, and (ii) determined features of an observed past context in which the associated vehicle was operating and/or in which the at least one past driver and/or past passenger was/were operating the associated vehicle contemporaneous with the at least one past driver and/or past passenger requesting the at least one past vehicle user interface action;
and
cause a user interface in the vehicle to generate an output based on the prediction of the future vehicle user interface action.

8 more elements

A method comprising:

determining, by one or more processors within, or in communication with, a vehicle, features indicative of a context in which the vehicle is currently operating and/or a context in which a driver and/or a passenger is/are currently operating the vehicle;
generating, by the one or more processors, a prediction of a future vehicle user interface action, from among a plurality of available vehicle user interface actions, wherein the prediction is generated based, at least in part, on:
the features indicative of the context in which the vehicle is currently operating or the context in which the driver and/or the passenger is/are currently operating the vehicle;
and
user action context parameters relating:
(i) at least one past vehicle user interface action requested by at least one past driver and/or past passenger of an associated vehicle, and (ii) determined features of an observed past context in which the associated vehicle was operating and/or in which the at least one past driver and/or past passenger was/were operating the associated vehicle contemporaneous with the at least one past driver and/or past passenger requesting the at least one past vehicle user interface action;
and
causing a user interface in the vehicle to generate an output based on the prediction of the future vehicle user interface action.

5 more elements

An article comprising:

a non-transitory storage medium comprising computer-readable instructions stored thereon, the instructions to be executable by one or more processors to:
determine features indicative of a context in which a vehicle is currently operating and/or a context in which a driver and/or a passenger is/are currently operating the vehicle;
generate a prediction of a future vehicle user interface action, from among a plurality of available vehicle user interface actions, wherein the prediction to be generated based, at least in part, on:
the features indicative of the context in which the vehicle is currently operating or the context in which the driver and/or the passenger is/are currently operating the vehicle;
and
user action context parameters relating:
(i) at least one past vehicle user interface action requested by at least one past driver and/or past passenger of an associated vehicle, and (ii) determined features of an observed past context in which the associated vehicle was operating and/or in which the at least one past driver and/or past passenger was/were operating the associated vehicle contemporaneous with the at least one past driver and/or past passenger requesting the at least one past vehicle user interface action;
and
cause a user interface in the vehicle to generate an output based on the prediction of the future vehicle user interface action.

6 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/066,959Filed 15 Dec 2022
Published: 20 Jun 2024
Term ends: Not estimatedThe source records don’t support an estimate.

Classification15 codes

G06N 20/20
Machine learning: ensemble learning
G07C 5/0808
Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working,…
B60K 35/20
Instruments specially adapted for vehicles; Arrangement of instruments in or on vehicles: output arrangements, i.e. from vehicle to user,…
G06N 5/022
Knowledge representation; Symbolic representation: knowledge engineering; Knowledge acquisition

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