The effects of driving experience on responses to a static hazard perception test

Hazard Perception Test (HPT): A Pilot Study in Brazil

“…Although there were significantly more male experts, female expert performance was exceedingly superior. Our results are partially in accordance with previous studies conducted in other countries (e.g., Johnston & Scialfa, 2016;Scialfa et al, 2012) and suggest that our adapted version can be employed in clinical settings where time pressure is much greater than in laboratory research.…”

“…Twenty one still images, from previous work (Scialfa et al, 2012), were selected to be the stimuli in this study. From those 21 scenes, two were eliminated from the set, with the criteria that those images were not found in the Brazilian driving environment (e.g., snow on the road and a traffic sign that is not used in Brazil).…”

Effects of driver age and experience in abrupt-onset hazards

“…Novice drivers (typically between 16 to 25 years old in most studies), compared to experienced drivers, are found to have inflexible and inefficient visual scanning strategies while driving (Crundall and Underwood, 1998;Pradhan et al, 2005;Scott et al, 2013); performed poorer in identifying latent hazards (Vlakveld, 2014); committed more driving errors with low situational awareness (Kass et al, 2007); are poorer at hazard perception (Borowsky et al, 2010;Scialfa et al, 2011Scialfa et al, , 2012; and have longer reaction times to peripheral stimuli (Patten et al, 2006). Underwood et al (2002) explained that this was due to novice drivers having inadequate mental models of the potential hazards on the roads.…”

The View from the Driver's Seat: What Good Is Salience?

“…To address this question, the present work sought a functional measure of the value of salient information in a driving‐related decision‐making task. Stimuli were traffic scenes photographed from the driver's vantage point, and the subjects' task was to make stop‐or‐go decisions about the depicted scenes (see Scialfa et al, , for a similar task also using static images). Images were manipulated to eliminate either the salient or the non‐salient regions, as identified by Itti and Koch's (; Walther & Koch, 2006) well‐validated computational salience model.…”