Dangerous and Aggressive Driving: Detecting the Interrelationship by Data Mining

Aggressive and dangerous driving is one of the most important human factors that has been studied in various studies. This article discusses the different levels of aggressive and dangerous driving and extracts decision rules using the decision tree method. The purpose of this paper is to determine the aggressive driving index and Dula dangerous driving index and to examine the conceptual model and the relationship between aggressive behavior and dangerous driving behavior using structural equations and decision tree. It will also answer the question of whether any driver with aggressive behavior is necessarily dangerous. In this study, 2,500 questionnaire data were collected from people with driving licenses in Qazvin, Iran. This study includes 14 variables within the framework by theories of planned behavior and risk homeostasis, which also includes Dula study variables. To determine the different levels of aggressive and dangerous driving behavior, the decision tree method was used and structural equations were used to investigate the conceptual model of variables and determine the relationship between aggressive behavior and dangerous driver behavior. The results show that attitude, age, personality traits, behavioral perception control, risky driving, aggressive driving and negative emotions/perceptions had a significant impact on aggressive and dangerous driving behavior. Accordingly, in the structural equation model, attitude as the most influential variable is associated with a load factor of 0.84 with aggressive behavior and a load factor of 0.75 with dangerous driving behavior. Dula variables have had a significant effect on determining the driver's behavior pattern by extracting decision-making rules.