2017 Volume 12 Pages 1884-1903
Speeding behaviors in mixed-traffic environments, where different types of vehicles participate, are influenced significantly by social-cognitive factors (e.g., drivers attitude, benefits). Quantitative measurement of these factors is there for important for traffic managers/controllers to determine optimal strategies to reduce the accident risks exposed to stakeholders (e.g. operators of a road network, users, and the public). This paper applies a statistical approach using regression analysis to quantify the influences of social-cognitive factors in a mixed-traffic environment. Precisely, in the proposed methodology, an integrated behavior analysis framework is developed based on the extension and combination of the theory of planned behaviors and the health belief model for a mixed-traffic environment. The methodology was tested with an example of mixed-traffic environment in Vietnam, where two wheels motor vehicles are dominant.