Systems and methods are provided for personalizing autonomous driving. The system can receive historical data on a driver of the vehicle's performance and population data indicating a population driving style. Speed data can be recorded as the driver of the vehicle drives the vehicle during a trial period. The historical data, population data, and speed data can be input into a machine learning model to determine a style for the driver. The system can receive one or more parameters from the machine learning model indicating the style. These parameters can be applied to the vehicle's automated driving system.


    Access

    Download


    Export, share and cite



    Title :

    SYSTEMS AND METHODS FOR PERSONALIZED AUTONOMOUS DRIVING


    Contributors:

    Publication date :

    2025-04-10


    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



    SYSTEMS AND METHODS FOR OPERATING AUTONOMOUS VEHICLES USING PERSONALIZED DRIVING PROFILES

    NAGY AKOS / BECKER JAN / RAJARAM SHETTY et al. | European Patent Office | 2017

    Free access

    SYSTEMS AND METHODS FOR OPERATING AUTONOMOUS VEHICLES USING PERSONALIZED DRIVING PROFILES

    NAGY AKOS / BECKER JAN / RAJARAM SHETTY et al. | European Patent Office | 2023

    Free access

    Systems and methods for operating autonomous vehicles using personalized driving profiles

    NAGY AKOS / BECKER JAN / RAJARAM SHETTY et al. | European Patent Office | 2019

    Free access

    SYSTEMS AND METHODS FOR OPERATING AUTONOMOUS VEHICLES USING PERSONALIZED DRIVING PROFILES

    NAGY AKOS / BECKER JAN / RAJARAM SHETTY et al. | European Patent Office | 2016

    Free access

    Personalized Autonomous Vehicle Control for Typical Driving Scenarios

    Haoran, Li / Wangling, Wei / Sifa, Zheng et al. | IEEE | 2022