Road Traffic Accidents (RTAs) constitute a significant public health conundrum due to their capricious nature. In the year 2022, India was the epicenter of 4,61,312 RTAs, leading to injuries for 4,43,366 individuals and the unfortunate demise of 1,68,491 lives. The dissection of accident data is instrumental in deciphering the underlying causative factors of these mishaps. This study endeavors to scrutinize the available RTAs data employing visualization techniques to discern causative factors, examine the repercussions of various vehicle types, and suggest efficacious methods to mitigate accidents. The data spanning from 2005 to 2022 was meticulously analyzed in two stages utilizing year-wise accident data procured from the Kerala State Crime Records Bureau and First Information Sheets (FIRs) from the Police Department. The initial phase of the research unveiled that driver error was a significant factor (70–90%) in accidents across diverse vehicle categories. The rate of persons involved per accident was notably high for RTAs involving heavy-duty vehicles (Avg. 1.42), which also exhibited elevated fatality rates. In the subsequent phase, analysis of FIRs highlighted key areas of concern that necessitate immediate attention to minimize driver distraction. These include mobile-phone usage while driving (27.4%), driving under the influence of alcohol (24.9%), and ergonomic issues related to driving (22.1%). The visualization of accident data underscored the exigency to tackle ergonomic problems associated with heavy-duty drivers. Among these, long driving hours (26.6%), poorly designed driving environments (22%), and incorrect driving postures (19.3%) were identified as the most influential factors. This study harnesses the power of predictive visualization to aid in accident prevention and facilitates real-time adjustments of variables to enhance data comprehension. By highlighting neglected factors and rectifying data biases, the study advocates for responsible data presentation and interpretation. Furthermore, it identifies the most socially impactful causes of RTAs and establishes a connection between driver-related factors and road safety.


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    Titel :

    Contributing Factors of Road Traffic Accidents: Exploration Through Data Visualization


    Weitere Titelangaben:

    Trans Indian Natl. Acad. Eng.


    Beteiligte:
    Chand, Arun (Autor:in) / Jayesh, S. (Autor:in) / Bhasi, A. B. (Autor:in)


    Erscheinungsdatum :

    01.06.2024


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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