Driver distraction by digital billboards? Structural equation modeling based on naturalistic driving study data: A case study of Iran

Abstract

Introduction: Digital billboards (DBs) are a competing factor for attracting drivers’ attention; evidence shows that DBs may cause crashes and vehicle conflicts because they catch drivers’ attention. Because of the complexity of a system that includes road conditions, driver features, and environmental factors, it is simply not possible to identify relationships between these factors. Thus, the present study was conducted to provide a well-organized procedure to analyze the effects of DBs on drivers’ behavior and measure factors responsible for drivers’ distraction in Babol, Iran, as a case study. Method: Corresponding data were collected through a Naturalistic Driving Study (NDS) of 78 participants when facing DBs (1,326 samples). These data were analyzed by applying structural equation modeling (SEM) to concurrently recognize relationships between endogenous and exogenous variables. Human, environmental, and road factors were determined as exogenous latent variables in a model to evaluate their influences on drivers’ distraction as an endogenous variable. Results: The results showed that road, environmental, and human factors reciprocally interact with drivers’ distraction, although the estimated coefficient of human factors was more of a factor than that of the other groups. Furthermore, younger drivers, beginner drivers, and male drivers (as human factors); night and unclear weather like a rainy day (as environmental factors); and installing DBs at complicated traffic positions like near-intersections (as road factors) were determined to be the main factors that increase the possibility of drivers’ distraction. Finally, model assessment was suggested using the goodness-of-fit indices.