%0 Journal Article
%T THE USE OF K-MEANS CLUSTERING ALGORITHM FOR IDENTIFYING THE TRAFFIC ACCIDENT PATTERNS: CASE OF THE SAKARYA CITY
%A Erman CO£¿KUN
%A H¨¹seyin Serdar GE£¿ER
%A Keziban SE£¿K£¿N CODAL
%A Samet G¨¹NER
%J -
%D 2018
%X The most common definition of traffic accidents is the fatality, injury or damage of one or more vehicles on the roads (Anderson, 2009). Traffic accidents cause loss of life and property both in the world and in our country. A total of 4577 fatal and injured traffic accidents occurred in the city center between 2006 and 2012 in Sakarya. A total of 6647 people were injured in these accidents and 62 people lost their lives (Sakarya Province Traffic Inspection Branch Directorate). However, it should be noted that this figure only covers citizens who have died at the site of the accident. This number is expected to increase when the survivors died in the hospital after the accident. In this study, which examines the traffic accidents occurred in the city of Sakarya between 2006 and 2012, the similarities between the traffic accidents will be investigated, and the main accident characteristics will be determined using these similarities. Therefore, it is aimed to identify similar accident groups and propose specific solutions to them. The main objective of the study is to investigate the similarity relations between traffic accidents occurring in the city and to provide a road map to the decision makers in the investments to be made to the developing city infrastructure based on this similarity relationship. In this study, it is planned to answer the following research questions: £¿ How many different clusters can be collected by using the similarity of Euclidean distance between traffic accidents? £¿ What is the weighted distribution of accidents under these clusters? £¿ How can the clusters be classified on the basis of districts? In this study, K-means clustering method was used in the analysis of traffic accidents. Clustering algorithm is a statistical method commonly used in accident analysis. This is because accidents show many similarities and differences in terms of environmental characteristics, vehicle characteristics, types of accidents and driver characteristics. The grouping of these similarities is important to determine the accident characteristics and to prevent the recurrence of these accidents. As a matter of fact, it is seen that clustering method is used widely in the accident analyzes conducted both in the world and in our country. International studies such as Kim and Yamashita (2007), Anderson (2009), Bocarejo and Diaz (2011), Figuera et al. (2011) and Mauro et al. (2013) can be given as example. The studies of Karpat and Y£¿lmaz (2002), Y£¿lmaz and Eri£¿o£¿lu (2003), Murat and £¿ekerler (2009), Atalay and Tortum (2010), Tortum vd. (2011) and
%K K¨¹meleme
%K K-means
%K Trafik
%K Kaza
%U http://dergipark.org.tr/jobs/issue/41643/415578