Structural Equation Modeling of Right-Turn Motorists at Unsignalized Intersections: Road Safety Perspectives

Abstract

This study aims to determine traffic behavior at the selected unsignalized intersection and the development of right-turn motorists (RTM) by adopting the logistic regression method (LRM) and structural equation modelling (SEM). In the early stage of the study, we analyzed the traffic behavior focusing on traffic volume and turning volume at the field site. This study involves five unsignalized intersections (UI), and it observes three types of turning volume: right turn volume (RTV) from a minor road onto a major road, left turn volume (LTV) from a minor road onto a major road, and right turn volume (RTV) from a major road onto a minor road. Although the SEM approach is among the popular scientific analysis and wisely applied in various fields of study, there is less attention to traffic behavior and road safety. An SEM model was developed for right-turn motorists using 812 datasets was developed, and variables that influenced the decision of right-turn motorists (RTM) were identified. Among the six variables analyzed in this statistical model, we identified gap, motorcycle rider, conflict lane change, and the traffic signal to be significant.

Keywords

• logistic regression method
• structural equation modeling
• traffic behavior