Systems and methods are provided for training a machine learning model to generate a planned trajectory for an ego vehicle that accounts for deviations from expert trajectories used to train the machine learning model. Examples include obtaining a first trajectory for a machine learning model, the first trajectory comprises a sequence of a plurality of vehicle states, and perturbing at least one of the plurality of vehicle states. Examples also include generating a second trajectory based on the at least one perturbed vehicle state and smoothening the second trajectory to correspond to the first trajectory. Examples further include training the machine learning model using the smoothened second trajectory to produce a planned trajectory for controlling a vehicle.


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    Title :

    GENERATING VEHICLE TRAJECTORIES TO ACCOUNT FOR DEVIATIONS IN TRAINING TRAJECTORIES


    Contributors:
    ZHANG YIMING (author) / HUO ZHAOYUAN (author) / AHUJA AAYUSH (author) / NARDI FLAVIO (author)

    Publication date :

    2025-06-26


    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



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