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

Methods, computing systems, and technology for automated vehicle action generation are presented. For example, a computing system may be configured to receive context data associated with a plurality of user interactions with a vehicle function of a vehicle. The context data may include data indicative of a plurality of user-selected settings for the vehicle function and data indicative of observed conditions associated with the respective user-selected settings. The computing system may be configured to generate, using a machine-learned clustering model, a user-activity cluster for the vehicle function based on the context data. The computing system may be configured to determine an automated vehicle action based on the user-activity cluster. The computing system may output command instructions for the vehicle to implement the automated vehicle action for automatically controlling the vehicle function in accordance with an automated setting based on whether the vehicle detects one or more triggering conditions.