Computing Systems And Methods For Generating User-Specific Automated Vehicle Actions Using Artificial Intelligence

A computer-implemented method comprising:

• receiving context data associated with a plurality of user interactions with a vehicle function of a vehicle over a plurality of instances in time, wherein the context data comprises data indicative of a plurality of user-selected settings for the vehicle function and data indicative of one or more observed conditions associated with the respective user-selected settings;
• generating, using a machine-learned clustering model, a user-activity cluster for the vehicle function based on the context data, the machine-learned clustering model being configured to identify the user-activity cluster based on at least a portion of the user-selected settings and at least a portion of the one or more observed conditions associated with the respective user-selected settings;
• determining an automated vehicle action based on the user-activity cluster, wherein the automated vehicle action is indicative of an automated setting for the vehicle function and one or more triggering conditions for automatically implementing the automated setting;
• and
• outputting command instructions for the vehicle to implement the automated vehicle action for automatically controlling the vehicle function in accordance with the automated setting based on whether the vehicle detects the one or more triggering conditions.

One or more non-transitory computer-readable media that store instructions that are executable by a control circuit to:

• receive context data associated with a plurality of user interactions with a vehicle function of a vehicle over a plurality of instances in time, wherein the context data comprises data indicative of a plurality of user-selected settings for the vehicle function and data indicative of one or more observed conditions associated with the respective user-selected settings;
• generate, using a machine-learned clustering model, a user-activity cluster for the vehicle function based on the context data, the machine-learned clustering model being configured to identify the user-activity cluster based on at least a portion of the user-selected settings and at least a portion of the one or more observed conditions associated with the respective user-selected settings;
• determine an automated vehicle action based on the user-activity cluster, wherein the automated vehicle action is indicative of an automated setting for the vehicle function and one or more triggering conditions for automatically implementing the automated setting;
• and
• output command instructions for the vehicle to implement the automated vehicle action for automatically controlling the vehicle function in accordance with automated setting based on whether the vehicle detects the one or more triggering conditions.