Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving and transportation systems to digitize and synergize connected automated vehicles. However, existing studies focus on the design of the automated vehicle, whereas the digitization of the human driver, who plays an important role in driving, is largely ignored. Furthermore, previous driver-related tasks are limited to specific scenarios and have limited applicability. Thus, a novel concept of a driver digital twin (DDT) is proposed in this study to bridge the gap between existing automated driving systems and fully digitized ones and aid in the development of a complete driving human cyber-physical system (H-CPS). This concept is essential for constructing a harmonious human-centric intelligent driving system that considers the proactivity and sensitivity of the human driver. The primary characteristics of the DDT include multimodal state fusion, personalized modeling, and time variance. Compared with the original DT, the proposed DDT emphasizes on internal personality and capability with respect to the external physiological-level state. This study systematically illustrates the DDT and outlines its key enabling aspects. The related technologies are comprehensively reviewed and discussed with a view to improving them by leveraging the DDT. In addition, the potential applications and unsettled challenges are considered. This study aims to provide fundamental theoretical support to researchers in determining the future scope of the DDT system


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles


    Contributors:
    Hu, Zhongxu (author) / Lou, Shanhe (author) / Xing, Yang (author) / Wang, Xiao (author) / Cao, Dongpu (author) / Lv, Chen (author)

    Published in:

    Publication date :

    2022-09-01


    Size :

    3590307 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





    Self-Driving Vehicles and Enabling Technologies

    Găiceanu, Marian | GWLB - Gottfried Wilhelm Leibniz Bibliothek | 2021

    Free access

    Self-Driving Vehicles and Enabling Technologies

    Găiceanu, Marian | TIBKAT | 2021

    Free access

    Self-Driving Vehicles and Enabling Technologies

    Gaiceanu, Marian | GWLB - Gottfried Wilhelm Leibniz Bibliothek | 2021

    Free access