Spatial Distribution and Cluster Analysis of Road Traffic Accidents in Khon Kaen Municipality, Thailand

Abstract

This study examines the spatial distribution and cluster analysis of road traffic accidents (RTAs) within Khon Kaen Municipality, Thailand, focusing on the top ten intersections with the highest RTAs. The analysis incorporates general information on RTAs, including gender, age group, type of vehicles involved, group of victims, and the time of day when the accidents occurred. Analyzing data on RTAs, we found that the majority of incidents occurred among males aged 21-30 years, with drivers being the most affected group and motorcycle accidents being the primary cause. Notably, RTAs peaked between midnight and 4:00 AM, potentially correlated with late-night activities. Global Moran’s I as well as Anselin local Moran’s I were adopted in the cluster analysis to identify hotspots, coldspots, and outliers among the intersections. Examination of RTA hotspots revealed concentration along major roads, particularly Highway No. 2 and Sricharn Road, suggesting the importance of road infrastructure in accident prevalence. Utilizing Anselin's Local Moran's I analysis, we identified a spatially random distribution of RTAs, indicating a lack of distinct spatial patterns or clustering. These findings provide valuable insights for policymakers and authorities to implement evidence-based measures aimed at enhancing road safety within and beyond Khon Kaen Municipality.