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

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.

Automated summary

This paper aims to use unsupervised machine learning, particularly k-means clustering, to analyze road accidents and understand relationships between variables. By describing clusters based on similarity measures in features, the study identifies differences between each cluster.