Some implementations of the disclosure are directed to reducing or removing time lag in vehicle velocity prediction by training a model for vehicle velocity prediction using labeled features that provide indication of a feature associated with a vehicle acceleration or deacceleration event. In one implementation, a method includes: receiving multiple time series datasets, each of the time series datasets including sensor data, GPS data, and vehicle state data collected over time; extracting features from each of the time series datasets that are indicative of a future velocity of a vehicle; labeling the extracted features of each of the time series datasets to indicate vehicle acceleration or deacceleration events; and after labeling the extracted features of each of the time series datasets, using at least a subset of the extracted and labeled time series datasets to train a machine learning model that predicts vehicle velocity some time into the future.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    Vehicle velocity predictor using neural networks based on V2X data augmentation to enable predictive optimal control of connected and automated vehicles


    Beteiligte:
    LIU KUAN X (Autor:in) / HUANG MIKE X (Autor:in) / KOLMANOVSKY ILYA V (Autor:in)

    Erscheinungsdatum :

    2020-10-27


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    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 / G05D SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES , Systeme zum Steuern oder Regeln nichtelektrischer veränderlicher Größen / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / H04W WIRELESS COMMUNICATION NETWORKS , Drahtlose Kommunikationsnetze






    Optimal Vehicle Dynamics and Powertrain Control for Connected and Automated Vehicles

    Zhao, Liuhui / Mahbub, A M Ishtiaque / Malikopoulos, Andreas A. | IEEE | 2019