This study aims to explore the association between distracted driving (including cognitive, visual, operational, and auditory distractions) and multi-source features of ride-hailing drivers, and to discover frequent patterns of distracted driving. To achieve this, a natural driving experiment was conducted, and an association rule mining (‘Apriori’ algorithm) was used to uncover hidden rules between distracted driving and the multi-source features (including emotion, valence, arousal, driving tasks, cumulative driving hours, velocity, longitudinal acceleration, lateral acceleration, heading rate, presence of intersections, traffic status, and driving time of day). Results indicate that distracted driving is prevalent among ride-hailing drivers in specific scenarios, including trips without passengers, non-intersection sections, driving for over 4 h, and congested traffic conditions. The emotional state of drivers has also been found to have an interesting association with distracted driving. For instance, cognitive and operational distraction were highly associated with positive driving emotions, but auditory distraction caused by passenger interference was highly associated with negative driving emotions. Moreover, there are variations in distracted driving patterns across different categories. These findings can help ride-hailing platforms develop more scientific and effective distracted driving monitoring and prevention strategies.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Understanding distracted driving patterns of ride-hailing drivers from multi-source data: Applying association rule mining


    Weitere Titelangaben:

    G. Xing et al.
    Journal of Transportation Safety & Security


    Beteiligte:
    Xing, Guanyang (Autor:in) / Chen, Shuyan (Autor:in) / Ma, Yongfeng (Autor:in) / Zhang, Chenxiao (Autor:in) / Xie, Zhuopeng (Autor:in) / Zhu, Yi (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    02.04.2024


    Format / Umfang :

    31 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Online car-hailing distracted driving behavior identification method based on multi-source data

    MA YONGFENG / WANG FAN / XING GUANYANG et al. | Europäisches Patentamt | 2024

    Freier Zugriff

    RIDE-HAILING SYSTEM AND RIDE-HAILING METHOD

    KAMATA NOBUHIDE / UEHARA YASUO / TANIMORI SHUNSUKE et al. | Europäisches Patentamt | 2020

    Freier Zugriff

    Investigating the trip configured causal effect of distracted driving on aggressive driving behavior for e-hailing taxi drivers

    Muhammad Sajjad Ansar / Yongfeng Ma / Shuyan Chen et al. | DOAJ | 2021

    Freier Zugriff

    RIDE HAILING MANAGEMENT DEVICE, PROGRAM, RIDE HAILING MANAGEMENT SYSTEM, AND RIDE HAILING MANAGEMENT METHOD

    NAKADOI TOSHIYUKI / KATO YOSHITSUGU / OSHIMA TAKAYA | Europäisches Patentamt | 2025

    Freier Zugriff

    RIDE-HAILING SYSTEM, RIDE-HAILING METHOD, AND COMPUTER PROGRAM

    SAKAMOTO AKIRA | Europäisches Patentamt | 2024

    Freier Zugriff