Identifying Hazardous Crash Locations Using Empirical Bayes and Spatial Autocorrelation

Abstract

Identifying and prioritizing hazardous road traffic crash locations is an efficient way to mitigate road traffic crashes, treat point locations, and introduce regulations for area-wide changes. A sound method to identify blackspots (BS) and area-wide hotspots (HS) would help increase the precision of intervention, reduce future crash incidents, and introduce proper measures. In this study, we implemented the operational definitions criterion in the Hungarian design guideline for road planning, reducing the huge number of crashes that occurred over three years for the accuracy and simplicity of the analysis. K-means and hierarchical clustering algorithms were compared for the segmentation process. K-means performed better, and it is selected after comparing the two algorithms with three indexes: Silhouette, Davies–Bouldin, and Calinski–Harabasz. The Empirical Bayes (EB) method was employed for the final process of the BS identification. Three BS were identified in Budapest, based on a three-year crash data set from 2016 to 2018. The optimized hotspot analysis (Getis-Ord Gi*) using the Geographic Information System (GIS) technique was conducted. The spatial autocorrelation analysis separates the hotspots, cold spots, and insignificant areas with 95% and 90% confidence levels.

Reliability-based analysis of horizontal curve design by evaluating the impact of vehicle automation on roadway departure crashes and safety performance

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Measurement of Accident Risk and a Case Study from Hungary

“…Road traffic crashes are the eighth leading cause of death worldwide, with more than 1 million people estimated to die on the world's roads each year; a further 20-50 million people suffer non-fatal injuries each year as a result of road accidents (Mekonnen, et al, 2023). Even if the loss of life is invaluable, it puts a value on the resources we are prepared to give up reducing the risk of this dreadful outcome; resources that we, both as individuals and as a society, are prepared to spend on traffic safety activities (Baranyai and Sipos, 2022).…”

Identification of hazardous road sites: a comparison of blackspot methodology of Narogong Road Bekasi and Johor Federal Roads

“…Identifying hazardous road locations typically entails key aspects such as defining the location of routes and areas, establishing "hazardous" criteria, such as using frequency, speed, speed quality control, or crash potential reduction methods, and considering into account relevant factors such as exposure, such as traffic volume and traffic mix [9]. It is also necessary to determine the severity of crashes by giving greater weight to fatal crashes than injury crashes and the time period of the crash [10]. While all of these factors are essential for scientific crash analysis, this study, which presents preliminary findings from a larger-scale experiment, concentrates just on the first, namely location definition.…”