Using fuzzy signal detection theory to determine why experienced and trained drivers respond faster than novices in a hazard perception test

Abstract

Drivers’ hazard perception ability, as measured in video-based simulations, correlates with crash involvement, improves with experience and can be trained. We propose two alternative signal detection models that could describe individual differences in this skill. The first model states that novice drivers are poorer at discriminating more hazardous from less hazardous situations than experienced drivers. The second model proposes that novice drivers require a higher threshold of danger to be present before they notice a situation is hazardous or before they are willing to classify a situation as hazardous. We applied a technique involving fuzzy signal detection analysis to differentiate between these two models when comparing novice and experienced drivers, and trained and untrained drivers, in various video-based hazard perception measures. The data favored the second model.