Determination of traffic accident black spots in Konya city using geographic information systems-supported spatial statistical methods

Traffic accidents are one of the most formidable challenges faced by modern societies in the contemporary world. Numerous efforts are underway to mitigate the substantial human and material losses they cause. Identifying areas with a high concentration of traffic accidents, commonly referred to as accident black spots, is a widely explored avenue for reducing the incidence of such accidents. Accurate identification of these points, which experience a significant number of accidents, is crucial for the effective organization of traffic safety policies. In this study, traffic accident black spots in the districts of Karatay, Meram, and Selçuklu, which constitute the city of Konya, have been identified. For this purpose, spatial statistical methods based on geographic information systems have been utilized. In addition to spatial autocorrelation indices such as Moran's I, Anselin Local Moran's I, Getis-Ord Gi, and Geary's C, Kernel Density Estimator, and spatial interpolation (IDW) methods have also been employed. The study dataset comprises information on fatal and injury-causing traffic accidents that occurred in the study area between 2017 and 2022. The findings of the analysis indicate that traffic accidents tend to concentrate in specific regions, forming statistically significant clusters in these areas. Within these regions of heightened accident occurrence, a total of 32 distinct traffic accident black spots were identified, and detailed information about these points is provided. The concluding section of this study presents conclusions and recommendations based on the findings and experiences gained throughout the process. Lastly, suggestions are offered to guide future research, aiming to contribute to the literature in the field.