An autonomous vehicle collects sensor data of an environment surrounding the autonomous vehicle including traffic entities such as pedestrians, bicyclists, or other vehicles. The sensor data is provided to a machine learning based model along with an expected turn direction of the autonomous vehicle to determine a hidden context attribute of a traffic entity given the expected turn direction of the autonomous vehicle. The hidden context attribute of the traffic entity represents factors that affect the behavior of the traffic entity, and the hidden context attribute is used to predict future behavior of the traffic entity. Instructions to control the autonomous vehicle are generated based on the hidden context attribute.


    Access

    Download


    Export, share and cite



    Title :

    NAVIGATION OF AUTONOMOUS VEHICLES USING TURN AWARE MACHINE LEARNING BASED MODELS FOR PREDICTION OF BEHAVIOR OF A TRAFFIC ENTITY



    Publication date :

    2021-11-18


    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 / G06K Erkennen von Daten , RECOGNITION OF DATA



    Navigation of autonomous vehicles using turn aware machine learning based models for prediction of behavior of a traffic entity

    ANTHONY SAMUEL ENGLISH / HARTMANN TILL S / MAAT JACOB REINIER et al. | European Patent Office | 2022

    Free access

    TURN AWARE MACHINE LEARNING FOR TRAFFIC BEHAVIOR PREDICTION

    ANTHONY SAMUEL ENGLISH / HARTMANN TILL S / MAAT JACOB REINIER et al. | European Patent Office | 2021

    Free access

    TURN AWARE MACHINE LEARNING FOR TRAFFIC BEHAVIOR PREDICTION

    ANTHONY SAMUEL ENGLISH / HARTMANN TILL S / MAAT JACOB REINIER et al. | European Patent Office | 2024

    Free access