This paper introduces a new method for driving style identification based on vehicle communication signals. The purpose of this method is to classify a trip, driven in a vehicle, into three driving style categories: calm, normal or aggressive. The trip is classified based on the vehicle class, the type of road it was driven on (urban, rural or motorway) and different types of driving events (launch, accelerating and braking). A representative set of parameters, selected to take into consideration every part of the driver-vehicle interaction, is associated to each of these events. Due to the usage of communication signals, influence factors, other than vehicle speed and acceleration (e.g. steering angle or pedals position), can be considered to determine the level of aggressiveness on the trip. The conversion of the parameters from physical values to dimensionless score is based on conversion maps that consider the road and vehicle types. These maps have been defined from a representative set of subjectively-rated test trips. The method used to define these maps is described as well. The correlation between driving style score and fuel consumption is then demonstrated. This correlation illustrates that the algorithm can be successfully used to differentiate distinct driving styles. Finally, different applications for driving style identification (DSI) algorithm are discussed.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Driving Style Identification Algorithm with Real-World Data Based on Statistical Approach


    Additional title:

    Sae Technical Papers


    Contributors:
    Kim, Bill (author) / Gao, Bo (author) / Fuente, David (author) / Shah, Nirav (author) / Ouali, Tarek (author)

    Conference:

    SAE 2016 World Congress and Exhibition ; 2016



    Publication date :

    2016-04-05




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Driving Style Identification Algorithm with Real-World Data Based on Statistical Approach

    Ouali, Tarek / Shah, Nirav / Kim, Bill et al. | British Library Conference Proceedings | 2016


    Driving Style Analysis by Classifying Real-World Data with Support Vector Clustering

    Feng, Yuxiang / Pickering, Simon / Chappell, Edward et al. | IEEE | 2018


    Intelligent driving style identification method based on natural driving data

    ZHANG SIYANG / ZHANG ZHERUI / ZHAO CHI | European Patent Office | 2025

    Free access

    Driving style identification algorithm based on factor analysis and machine learning

    ZHAO JIAN / CHEN ZHICHENG / ZHU BING | European Patent Office | 2020

    Free access

    Driving style identification method and system based on electroencephalogram data

    QI GEQI / YANG LIU / LI PEIHAO et al. | European Patent Office | 2023

    Free access