In this paper, the road traffic accident datasets for Germany and India are compared as a sample for developed and developing countries. Data wrangling and data analysis are performed on the adjusted OECD datasets to compare the number of road accidents, motor vehicles per road length, and death rates in both the countries and the factors influencing it. As per the analysis, the death instances in India are high due to road accidents in spite of less registered vehicle per road length. Besides, the research reviews the road accidents in developed countries, for which the dataset maintained by German Government are fetched to study the population that generally use the local public transport to commute to office, and also the sociodemographic data are collected to gather the preference to use the local transport, in developed country. The objective of the research is to evaluate and understand the various data distributions in the dataset and to analyze the different factors and attributes responsible for the accident. External independent variables like the weather, lighting conditions, etc., are excluded as do not show major impacts on the road accidents. By performing the correlation analysis of the dependent variables like category, type, and kind of the road traffic accidents, it is evident that majority of accidents occur during the rush hours.

    The paper reviews the road accident data of Germany in 2019, and analysis showcases that the group involved in road accidents is of the normal commuters working from 9 to 5 time period.


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    Title :

    Data Correlation Analysis to Curb Road Accidents


    Additional title:

    Lect. Notes in Networks, Syst.


    Contributors:

    Conference:

    International Conference on Communication, Electronics and Digital Technology ; 2023 ; New Delhi, India February 09, 2023 - February 10, 2023



    Publication date :

    2023-06-27


    Size :

    25 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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