arxiv:2108.03490

Clustering Algorithms to Analyze the Road Traffic Crashes

Published on Aug 7, 2021

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Abstract

The paper recommends DBSCAN and OPTICS for clustering accident-prone areas due to their effectiveness and efficiency over existing techniques.

AI-generated summary

Selecting an appropriate clustering method as well as an optimal number of clusters in road accident data is at times confusing and difficult. This paper analyzes shortcomings of different existing techniques applied to cluster accident-prone areas and recommends using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Ordering Points To Identify the Clustering Structure (OPTICS) to overcome them. Comparative performance analysis based on real-life data on the recorded cases of road accidents in North Carolina also show more effectiveness and efficiency achieved by these algorithms.

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