Introduction: Driving behavior theoretical models consider attitudes as an important determinant of driver behavior. Moreover, the association between the self-reported tendency to commit violations and accident involvement is widely recognized. This research investigates drivers’ self-reported behavior and attitudes to risky behaviors related to the trafﬁc violations of speeding, drink-driving, and cell phone use using cluster analysis. Method: A sample of 601 Greek drivers participating at the SARTRE 4 pan-European survey is utilized. The analysis identiﬁed three clusters of drivers. Drivers in Cluster 1 commit trafﬁc violations more often; drivers inCluster 2 favor trafﬁc violation countermeasures while having moderate views toward compliance with trafﬁc rules and drivers in Cluster 3 strongly support trafﬁc violation countermeasures and also have strong viewstoward compliance with trafﬁc rules. Risky behaviors and related attitudes that differentiate the three distinctgroups of drivers (clusters) were determined. Results: The ﬁndings indicate that differences in attitudes and behaviors may be attributed to factors such as age, gender, and area of residence. The research ﬁndings also provided some insight about the current level of drivers’ attitudes to trafﬁc violations, especially those that negatively affect trafﬁc safety. The pattern of their views on violations may form the basis of risk behavior-related interventions tailored to the identiﬁed groups, aiming at informing, educating, and raising the awareness ofthe public. Impact on Industry: Agencies focused on safety interventions could exploit this information in designing and implementing education campaigns, enforcement programs and in deﬁning relevant priorities.
|Tags||driver behaviour, statistical modelling|