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    Volume 1, Issue 1, IECE Transactions on Intelligent Unmanned Systems
    Volume 1, Issue 1, 2024
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    Jinchao Chen
    Jinchao Chen
    School of Computer Science, Northwestern Polytechnical University, Xi’an 710129, China
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    IECE Transactions on Intelligent Unmanned Systems, 2024, Volume 1, Issue 1: 4-15

    Free to Read | Review Article | 07 July 2024
    Advancements and Perspectives in Fatigue Driving Detection: A Comprehensive Review
    by
    IECE Author Xiao Yan 1 *
    IECE Author Ashardi bin Abas 1
    1 University Pendidikan Sultan Idrts, 35900, Malaysia
    * Corresponding Author: Xiao Yan, [email protected]
    DOI: https://doi.org/10.62762/TIUS.2024.767724
    Received: 19 April 2024, Accepted: 25 June 2024, Published: 07 July 2024  
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    Abstract
    Driver fatigue is a significant contributor to road accidents worldwide. Timely detection and alert systems for driver fatigue can substantially enhance driving safety and reduce traffic-related casualties. This article presents a comprehensive review of the recent advancements in driver fatigue detection technologies. It categorizes and evaluates detection methods based on physiological signals, behavioral characteristics, vehicle dynamics, and information fusion techniques. Additionally, it scrutinizes the prevalent datasets and methodologies employed in fatigue detection, offering valuable insights for future research directions. Our analysis emphasizes the importance of integrating multimodal data to improve detection accuracy and reliability, underlining the potential of information fusion approaches in developing robust fatigue detection systems. This synthesis aims to serve as a foundational reference for researchers venturing into the domain of driver fatigue detection, paving the way for innovative solutions to combat fatigue-induced road accidents.
    Graphical Abstract
    Advancements and Perspectives in Fatigue Driving Detection: A Comprehensive Review
    Keywords
    Fatigue driving
    Detection method
    Information fusion
    Dataset
    Funding
    This work was supported without any funding.
    Cite This Article
    APA Style
    Yan, X., & Abas, A. (2024). Advancements and Perspectives in Fatigue Driving Detection: A Comprehensive Review. IECE Transactions on Intelligent Unmanned Systems, 1(1), 4–12 https://doi.org/10.62762/TIUS.2024.767724
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