The described aspects and implementations enable training and deploying of accurate one-shot models capable of predicting trajectories of vehicles and other objects in driving environments. The disclosed techniques include, in one implementation, obtaining training data that includes a training input representative of a driving environment of a vehicle and one or more ground truth trajectories associated with a forecasted motion of the vehicle within the driving environment. The one or more ground truth trajectories are generated by a teacher model using the training input. The techniques further include training, using the training data, a student model to predict one or more trajectories of the vehicle and/or objects in the driving environment of the vehicle.


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    Title :

    DISTILLATION-TRAINED MACHINE LEARNING MODELS FOR EFFICIENT TRAJECTORY PREDICTION


    Additional title:

    DURCH DESTILLATION BESCHRÄNKTE MASCHINENLERNMODELLE ZUR EFFIZIENTEN TRAJEKTORIENVORHERSAGE
    MODÈLES D'APPRENTISSAGE AUTOMATIQUE ENTRAÎNÉS PAR DISTILLATION POUR PRÉDICTION DE TRAJECTOIRE EFFICACE


    Contributors:
    YAN QIAOJING (author) / TIAN RAN (author) / GUAN YUN JIA (author) / MNEIMNEH MAHER (author)

    Publication date :

    2025-06-18


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    English


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / 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



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