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.
DISTILLATION-TRAINED MACHINE LEARNING MODELS FOR EFFICIENT TRAJECTORY PREDICTION
DURCH DESTILLATION BESCHRÄNKTE MASCHINENLERNMODELLE ZUR EFFIZIENTEN TRAJEKTORIENVORHERSAGE
MODÈLES D'APPRENTISSAGE AUTOMATIQUE ENTRAÎNÉS PAR DISTILLATION POUR PRÉDICTION DE TRAJECTOIRE EFFICACE
18.06.2025
Patent
Elektronische Ressource
Englisch
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 |
AUTONOMOUS VEHICLE TRAJECTORY PLANNING USING NEURAL NETWORK TRAINED BASED ON KNOWLEDGE DISTILLATION
Europäisches Patentamt | 2025
|A Machine Learning Approach to Trajectory Prediction
AIAA | 2013
|Learning Probabilistic Intersection Traffic Models for Trajectory Prediction
ArXiv | 2020
|