SYSTEMS AND METHODS FOR ADAPTIVE CRUISE CONTROL BASED ON ONLINE LEARNING PREFERENCE

A system and method for online learning adaptive cruise control (ACC) for driving a vehicle includes one or more non-transitory memories storing an ACC model pool comprising one or more ACC models, and one or more processors. The one or more processors operably causes the system to generate, using a trained meta algorithm and based on historical user inputs and user preferences of a user, one or more personalized ACC models associated with the user, and include the one or more personalized ACC models in the ACC model pool, determine whether the user triggers a real-time ACC disengagement, in response to determining that the user triggers the real-time ACC disengagement, select, based on real-time user inputs, a predicted ACC model from the ACC model pool including the one or more personalized ACC models, and engage the vehicle with the predicted ACC model.