Analysis of Fatal and Injury Traffic Accidents in Istanbul Sarıyer District with Spatial Statistics Methods

Abstract

Traffic accidents, which continue to increase from year to year in Turkey and in the world, have become a huge problem that can result in serious traumas, injuries, and deaths, as well as their material and moral consequences. Many studies have been carried out in the world and in Turkey to reduce the number of traffic accidents, but these studies have not been very effective in reducing accidents. In this study, 3105 fatal or injured traffic accidents between 2010–2017 in Sarıyer district of Istanbul, Turkey’s largest city in terms of population, were discussed. We analyzed the statistical information on the subject in detail within the framework of geographic information systems. It has been tried to determine the sections where traffic accidents are concentrated in this region with studies based on spatial methods. Thematic accident map was created according to the accident types. In this context, the advantages and disadvantages of these methods were compared using Point Density, Kernel Density, Getis Ord Gi*, and Anselin Local Moran’s I (LISA) Spatial Autocorrelation. In addition, in order to observe the change in accidents, thematic accident and Kernel Density maps were created separately according to accident occurrence types in the beginning and last year. From this point of view, the changes that occurred in the accidents were interpreted. The current study determined that the most accidents were on some streets and these streets divided into regions in a plan. The cases were examined with statistical analyses according to accident types and using the Kernel Density method. In addition, it has been observed that Kernel Density method gives better visual results than other spatial methods. In this study, spatial analysis and statistical analysis methods were used to evaluate traffic accidents more realistically. The day of the week effect and month of the year effect on traffic accidents was investigated for the first time. In addition, it is proposed to bring a new approach to the prevention of traffic accidents by using hotspot, accident type, and day of the week effect.

Data Mining as a Method for Comparison of Traffic Accidents in Şişli District of Istanbul

“…Day of the week anomaly in traffic accidents was investigated through the linear regression equation (1) using dummy variables (Evci, 2020;Ersen, Büyüklü, & Taşabat, 2021). In regression analysis, the dependent (affected) variable is frequently affected by qualitative variables as well as numerical values.…”

“…Since analyses will be made based on big data with this study, we can call the accident analysis as "Accident Analytics". Another reason why accident analysis is named as accident analytics in the study is that traffic accidents cannot be determined in advance in terms of place and time and cannot be interpreted well enough (Ersen, Büyüklü, & Taşabat, 2021). Accident analytics, which enables traffic accident analysis based on concrete traffic accident data and traffic information, will help you to understand the accidents in detail and to determine what can be done to prevent future traffic accidents and will help to minimize traffic accidents (Ersen, Büyüklü, & Taşabat, 2021).…”

“…Another reason why accident analysis is named as accident analytics in the study is that traffic accidents cannot be determined in advance in terms of place and time and cannot be interpreted well enough (Ersen, Büyüklü, & Taşabat, 2021). Accident analytics, which enables traffic accident analysis based on concrete traffic accident data and traffic information, will help you to understand the accidents in detail and to determine what can be done to prevent future traffic accidents and will help to minimize traffic accidents (Ersen, Büyüklü, & Taşabat, 2021). Traffic Accident Analytics aims to create safe road and vehicle usage opportunities by establishing smart systems using the latest technologies based on the most appropriate scientific methods.…”

“…Traffic Accident Analytics aims to create safe road and vehicle usage opportunities by establishing smart systems using the latest technologies based on the most appropriate scientific methods. While doing this, it discovers the meaningful pattern in the data by using the available data structures, optimization, simulation methods, data analytics and data mining (Ersen, Büyüklü, & Taşabat, 2021). In these analyses, methods such as the accident frequency (number) method and accident recurrence rate method are used to determine accident points.…”

“…In order to develop effective road safety measures that can be used to reduce traffic accidents, it is necessary to identify the regions (hot spots) where the accidents are concentrated (Xie & Yan, 2008). The Kernel Density estimation method is the most common method used in spatial analysis studies in GIS and it is known to give successful results in determining hot spots (Ersen, Büyüklü, & Taşabat, 2021). The Kernel Density estimation method is based on the process of determining the accident intensity by weighting in a determined impact area.…”