Traffic Behaviour Analysis using Logistic Regression Method(LRM) and Structural Equation Modelling (SEM)

Abstract

This study aims to determine traffic behaviour 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 analysed the traffic behaviour 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 behaviour and road safety. An SEM model for right-turn motorists using 812 datasets was developed and variables that influenced the decision of right-turn motorists (RTM) were identified. Out of the six variables analysed in this statistical model, we identified gap, motorcycle rider, conflict lane change and the traffic signal to be significant.