Evaluating the Powerful Prediction of Integrated Behavioral Model for Risky Road Behaviors

Risky behaviors lead to road traffic safety accidents in Vietnam. Some individual risky behaviors were studied through distinct models to understand road user behaviors and to propose measurements for traffic safety improvement. This paper generally aimed to evaluate powerful prediction of Integrated Behavioral Models (IBM) for three risky behaviors i.e., driving after drinking (DAD), illegal changing direction (IDC), and speeding. Potential countermeasures will be proposed based on results. Results indicate that IBM successfully explains risky behaviors, especially for DAD. Among explainable variables, perceived severity is the only factor affecting all three risky behaviors.