Assessing the relationship between heavy vehicle driver sleep problems and confirmed driver behavior measurement tools in Iran

Abstract

Road traffic crashes have become an important public health problem. By studying the statistics of heavy vehicle crashes in the world, it becomes obvious that although heavy vehicle drivers experience fewer crashes than private car drivers, a large percentage of heavy vehicle crashes leads to death. So, it is important to identify the driving characteristics of heavy vehicle drivers. In this study, 474 Iranian truck drivers were interviewed face to face. Response rate of the survey was 80%, the participants who answered the questions on two behavioral questionnaires: Driver Behavior Questionnaire (DBQ) and Attention-Related Driving Error Scale (ARDES). Also, two sleep assessing questionnaires, Global Dissatisfaction with Sleep (GSD) and the Berlin Questionnaire, were completed. Confirmatory Factor Analysis (CFA) was used to confirm the validity of DBQ and ARDES for Iranian heavy vehicle drivers. After that, a Structural Equation Modeling (SEM) was used to identify the influence of sleep characteristics on truck driver behaviors. Results showed that more truck drivers are dissatisfied with their sleep, the more daily fatigue they suffer, and consequently, the more errors, slips, violations, and inattention they exhibit. Similar result trend was obtained for driver exposure. Also, the results showed that the more expensive a truck is, the less daily fatigue felt by the driver of the truck. Consequently, this leads to less aberrant driving behavior and inattention during driving.