Ensuring the effectiveness of adaptive algorithms for advanced driver assistance systems(ADAS)requires online recognition of driving styles. The article discusses studies carried out during real driving cyclesbased onthe GPS parameters and OBD system dataof a hybrid vehicle. The work focuses on the search for measures of the speed and acceleration signals of the car and the measures determined on their basis thatbest describe the driving style responsible for thevehicle traffic safety and ecological safety.Relations betweenthe type of driver, driving dynamics,and fuel consumptionwere studied. The driver's categorization was based on astatistical analysis of input signals and mean tractiveforce (MTF) by clustering.


    Access

    Download


    Export, share and cite



    Title :

    DRIVING STYLE ANALYSIS AND DRIVER CLASSIFICATION USING OBD DATA OF A HYBRID ELECTRIC VEHICLE


    Contributors:


    Publication date :

    2020




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    Unknown




    Driver classification and driving style recognition using inertial sensors

    Van Ly, Minh / Martin, Sujitha / Trivedi, Mohan M. | IEEE | 2013


    DRIVER CLASSIFICATION AND DRIVING STYLE RECOGNITION USING INERTIAL SENSORS

    Ly, M. / Martin, S. / Trivedi, M. et al. | British Library Conference Proceedings | 2013


    Hybrid electric vehicle driving style identification method and system

    LOU DIMING / CHEN ZHILIN / ZHANG YUNHUA et al. | European Patent Office | 2023

    Free access

    Classification of Assistance System Acceptability and Elderly Drivers Driving Style

    Hashimoto, N. / Kato, S. / Tsugawa, S. et al. | British Library Conference Proceedings | 2009


    METHOD FOR CONTROLLING HYBRID ELECTRIC VEHICLE USING DRIVING TENDENCY OF DRIVER

    CHOI YONG KAK / HAN HOON / PARK IL KWON | European Patent Office | 2015

    Free access