Clustering analysis of urban drivers regarding drivers' risk-taking behavior and driving fines

The aim of the present study is firstly to evaluate the relationship between drivers' risk-taking and driving offenses among drivers in 20 provinces of Iran using a survey based on a questionnaire study regarding demographic characteristics, risk-taking behavior, habits and safety information of drivers. Then, the relationship between drivers' risk-taking and related offenses is assessed using statistical tests such as Chi-square, Kruskal-Wallis, and U-Mann-Whitney. Finally, K-means clustering analysis is taken into consideration based on the relationship between drivers' risk-taking and driving offenses. In addition, the responses of drivers through increasing fines have been studied? Whether or not drivers agree or disagree has led to the classification of their behavioral characteristics and risk-taking behavior. Therefore, results showed that drivers were classified into four clusters based on behavioral characteristics in risk-taking and risk acceptance using the K-means clustering analysis. Clusters 1, 2, and 3 were named relatively high-risk, low-risk, and safe groups, respectively, and cluster 4 was named unsafe or high-risk group. Thus, clusters 3, 2 and 1 agreed on the effect of fines on the number of accidents, while clusters 4 opposed this effect, respectively. The safe cluster characteristics could be expressed as follows: At any time, drivers were careful about driving rules. At crossroads, they followed the right of way for others. At any time, they paid attention to driving traffic signs. When they approached the crossroad and saw the yellow lights, they stopped and they did not overtake the vehicle moving uphill. However, in the fourth cluster or unsafe cluster, the behavioral characteristics were totally contrary to the safe cluster's drivers.