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US 12,043,285 B2Granted
Vehicles that can be customized and personalized via mobile user profiles
AssigneeMicron Technology, Inc.
InventorRobert Richard Noel Bielby
Life of this patent
Estimating the term…
Abstract
A vehicle that can be customized and personalized via a mobile user profile. The vehicle can include a body, a powertrain, vehicle electronics, and a computing system. The computing system of the vehicle can be configured to: receive data fields of a driver profile of a user from a mobile device; estimate, using machine learning, configurations of vehicle functions for the vehicle according to the data fields; and control settings of a set of components of the vehicle, via the vehicle electronics, according to the estimated configurations.
Claims14
A system comprising:
- at least one processing device configured on a first vehicle;
- and
- memory containing instructions configured to instruct the at least one processing device to:
- receive, from a mobile device of a user, signaling indicative of settings for components of the first vehicle;
- wherein at least a portion of the settings for the components of the first vehicle is from user entered data or sensor generated data from the first vehicle and at least a portion of the settings for the components of the first vehicle is an output from first vehicle machine-learning processing using input comprising at least one data field corresponding to a setting for a component of the first vehicle and at least one data field corresponding to a setting for a component of another vehicle;
- wherein the mobile device is configured to store, in data fields of a mobile user profile, the settings for the components of the first vehicle received from the first vehicle;
- wherein the signaling indicative of the settings for the components of the first vehicle comprising input to the first vehicle machine-learning processing comprises internet browsing history or social media preferences of the user indicating:
- whether the user has online activities related to sports cars in the internet browsing history or the social media preferences of the user;
- whether the user has online activities related to fuel economy in the internet browsing history or the social media preferences of the user;
- and
- wherein the settings for the components of the first vehicle comprises a preferred driving mode, in a range between:
- a sports or performance driving mode;
- and
- a fuel economy mode;
- and wherein the preferred driving mode is determined based at least in part on online activities of the user related to sports cars and fuel economy in the internet browsing history or social media preferences;
- determine, based on the received signaling, new settings using second vehicle machine-learning processing, wherein the settings for the components of the first vehicle comprise inputs to the second vehicle machine-learning processing, and the new settings correspond to an output from the second vehicle machine-learning processing;
- and
- provide the new settings to the mobile device to cause the mobile device to store the new settings in the mobile user profile configured in the mobile device;
- wherein in response to the mobile device being securely connected to a second vehicle, the mobile user profile stored in the mobile device is to configure, based on the new settings, components of the second vehicle to dynamically transform the second vehicle to behave according to the preferred driving mode.
16 more elements
A method comprising:
- configuring, in response to a mobile device of a user being securely connected to a first vehicle, components of the first vehicle to dynamically transform the vehicle to behave according to a preferred driving mode identified via a mobile user profile configured in the mobile device, via:
- receiving, from the mobile device of the user and by a computing system of the first vehicle, signaling indicative of settings for components of a second vehicle;
- wherein the mobile device is configured to store, in data fields of the mobile user profile, the settings for the components of the second vehicle received from the second vehicle;
- wherein at least a portion of the settings for the components of the second vehicle is from user entered data or sensor generated data from the second vehicle and at least a portion of the settings of the components for the second vehicle is an output from machine-learning processing using input comprising at least one data field corresponding to a setting for a component of the second vehicle and at least one data field corresponding to a setting for a component of another vehicle;
- wherein the signaling indicative of the settings for the components of the second vehicle comprising input to the machine-learning processing comprises internet browsing history or social media preferences of the user indicating:
- whether the user has online activities related to sports cars in the internet browsing history or the social media preferences of the user;
- whether the user has online activities related to fuel economy in the internet browsing history or the social media preferences of the user;
- and
- wherein the settings for the components of the second vehicle comprises the preferred driving mode, in a range between:
- a sports or performance driving mode;
- and
- a fuel economy mode;
- and wherein the preferred driving mode is determined based at least in part on online activities of the user related to sports cars and fuel economy in the internet browsing history or social media preferences;
- estimating, based on the received signaling, a configuration of vehicle functions for the first vehicle, wherein the settings for components of the second vehicle comprise an input to first vehicle machine-learning processing, and the configuration corresponds to an output from the first vehicle machine-learning processing;
- and
- controlling, by the computing system based on the configuration, the components of the first vehicle to dynamically transform the first vehicle to behave according to the preferred driving mode.
13 more elements
A system comprising:
- a mobile device, having:
- a display configured to present a user interface to a user;
- at least one processing device;
- and
- memory containing instructions configured to instruct the at least one processing device to:
- select, according to user input received via the user interface, data fields of a mobile user profile configured in the mobile device and corresponding to a first vehicle, the data fields comprising settings for components of a second vehicle, the settings for the components of the second vehicle being received from the second vehicle and stored in the mobile device;
- wherein at least a portion of the settings for the components of the second vehicle is from user entered data or sensor generated data from the second vehicle and at least a portion of the settings for the components of the second vehicle is an output from machine-learning processing using input comprising at least one data field corresponding to a setting for a component of the second vehicle and at least one data field corresponding to a setting for a component of another vehicle;
- wherein the data fields for the settings for the components of the second vehicle comprising input to the machine-learning processing comprises internet browsing history or social media preferences of the user indicating:
- whether the user has online activities related to sports cars in the internet browsing history or the social media preferences of the user;
- whether the user has online activities related to fuel economy in the internet browsing history or the social media preferences of the user;
- and
- wherein the settings for the components of the second vehicle comprises a preferred driving mode, in a range between:
- a sports driving mode;
- a performance driving mode;
- and
- a fuel economy mode;
- and wherein the preferred driving mode is determined based at least in part on online activities of the user related to sports cars and fuel economy in the internet browsing history or social media preferences;
- estimate a configuration for vehicle functions of the first vehicle, wherein the data fields associated with the second vehicle comprise input to first vehicle machine-learning processing, and the configuration corresponds to an output of first vehicle machine-learning processing;
- and
- send, to the first vehicle, signaling indicative of the configuration, wherein the first vehicle is configured to, based on the configuration, control settings of components of the first vehicle.
17 more elements
Dependencies are inferred from the claim text.