The alarming rise in worldwide road traffic accidents poses serious challenges to numerous aspects of human existence. However, there has been a lack of attention paid to the important aspects of traffic characteristics, causation analysis, accident severity analysis, and the relationships between diverse causal factors. The road accident severity prediction system can be a significant analytical resource for traffic analysts and researchers aimed at identifying the major elements of road accident severity to improve road safety for automobiles as well as individuals. In this paper, we proposed effective deep-learning models for the tabular data to predict the severity of road accidents and our experimental results show the proposed method outperformed prior research works.


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    Titel :

    Advancing Road Safety: Road Accident Severity Prediction Using Deep Learning Models


    Beteiligte:


    Erscheinungsdatum :

    24.09.2024


    Format / Umfang :

    641063 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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