The goal of this paper is to use the unsupervised machine learning method in road accident analytics, especially using k-means clustering to identify patterns and understand the relationships between variables recorded by the UK police department. These include features like number of casualties, number of vehicles, age of vehicle and age bracket of the driver. We aim to describe clusters of accidents based on similarity measures in the features and identify what separates each one.


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    Titel :

    Traffic Accidents Analytics in UK Urban Areas using k-means Clustering for Geospatial Mapping


    Beteiligte:


    Erscheinungsdatum :

    21.01.2021


    Format / Umfang :

    833933 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Using mapping systems to analyse child traffic safety in urban areas

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    Street lighting as means of reducing traffic accidents

    von der Trappen, E. | Engineering Index Backfile | 1952


    Risk factors in urban road traffic accidents

    Vorko-Jovi, Ariana | Online Contents | 2006


    Urban development and traffic accidents in Brazil

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