Exploring Road Traffic Accidents Hotspots Using Clustering Algorithms and GIS-Based Spatial Analysis
Hussien Kamh, Saleh H. Alyami, Afaq Khattak, Mana Alyami, Hamad Almujibah
Abstract
This study conducts a comprehensive spatial analysis of road traffic accidents (RTAs) in Najran, a city emblematic of rapid urbanization in Saudi Arabia, which is facing significant public safety challenges due to an increase in vehicular traffic. By means of a dataset from 2022, we explore the spatial distribution of RTAs across the city’s districts by employing advanced clustering algorithms, including Density-based Spatial Clustering of Applications with Noise (DBSCAN) and Hierarchical Agglomerative Clustering (HAC), as well as GIS-based density analysis, proximity analysis, and spatial interpolation, to unveil accident hotspots and disparities in emergency service coverage. Our findings reveal that <xref ref-type="disp-formula" rid="deqn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(1)</xref> the HAC model, based on the Silhouette and Calinski-Harabasz Scores, performs better in identifying accident hotspots; <xref ref-type="disp-formula" rid="deqn2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(2)</xref> significant concentrations of accidents are observed along major highways and arterial roads, pinpointing critical hotspots within the city’s fabric; <xref ref-type="disp-formula" rid="deqn3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(3)</xref> proximity analysis indicates gaps in the coverage of ambulance services and public hospitals relative to high-incident areas; <xref ref-type="disp-formula" rid="deqn4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(4)</xref> through spatial interpolation, detailed visualizations of RTA distributions are provided, revealing diverse accident patterns across Najran. The study highlights the critical role of spatial analysis in identifying high-risk areas and provides valuable insights for transport planners and public safety officials, supporting the development of targeted strategies to improve road safety and enhance emergency service responses.