Hazard perception and prediction model based on cognitive components of male BRT drivers.

Abstract

Objectives: Hazard perception is a crucial skill for drivers and is typically measured using computer-based hazard perception tests. In these tests, drivers identify potential hazards in video clips recorded from the driver's perspective. Recently, researchers have also focused on another driver attribute called "hazard prediction." In hazard prediction tests, each scenario pauses just before a potentially dangerous event, and drivers must predict the subsequent events. Urban bus rapid transit (BRT) systems in Iran operate on dedicated routes that present specific hazards, such as sudden pedestrian crossings, motorcycle traffic, and emergency vehicles. Therefore, investigating the hazard perception and prediction abilities of BRT drivers can yield valuable insights to improve safety and reduce accidents.

Methods: This study was conducted in Tehran, Iran, involving 187 urban BRT drivers. Hazard perception and prediction tests were designed, and demographic as well as cognitive questionnaires were administered to assess driver characteristics.

Results: The data were analyzed using SmartPLS software and structural equation modeling. The final structural equation model for hazard perception indicated that social cognition, planning, and inhibitory control were the most influential factors. For hazard prediction, sustained attention, cognitive flexibility, inhibitory control, decision-making, and memory emerged as the most significant variables.

Conclusions: The results of this research can inform the training, testing, and evaluation of urban BRT drivers.