A system generates a first variant of a first machine learning (ML) model, the first variant associated with an initial hyperparameter value. The system determines a prediction metric for the first variant of the first ML model, the prediction metric indicating an accuracy of the behavior prediction. The system generates an estimated simulation metric for the first variant of the first ML model by applying a second ML model to the prediction metric. The system identifies a first hyperparameter associated with a second variant of the first ML model, the second variant of the first ML model having a corresponding prediction metric and a corresponding estimated simulation metric that meet a first predetermined criteria, the second variant of the first ML model is used by an autonomous driving vehicle (ADV) for behavior prediction.


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    Title :

    MULTI-LEVEL OPTIMIZATION FRAMEWORK FOR BEHAVIOR PREDICTION IN AUTONOMOUS DRIVING


    Contributors:
    CAO YU (author) / LI ANG (author)

    Publication date :

    2024-06-27


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen




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