Citation

Charlton SG, Starkey NJ, Perrone JA, Isler RB. Transp. Res. F Traffic Psychol. Behav. 2014; 25: 50-64.

Copyright

(Copyright © 2014, Elsevier Publishing)

DOI

10.1016/j.trf.2014.05.003

PMID

unavailable

Abstract

It has long been presumed that drivers' perceptions of risk play an important role in guiding on-road behaviour. The answer to how accurately drivers perceive the momentary risk of a driving situation, however, is unknown. This research compared drivers' perceptions of the momentary risk for a range of roads to the objective risk associated with those roads. Videos of rural roads, filmed from the drivers' perspective, were presented to 69 participants seated in a driving simulator while they indicated the momentary levels of risk they were experiencing by moving a risk meter mounted on the steering wheel. Estimates of the objective levels of risk for the roads were calculated using road protection scores from the KiwiRAP database (part of the International Road Assessment Programme). Subsequently, the participants also provided risk estimates for still photos taken from the videos. Another group of 10 participants viewed the videos and photos while their eye movements and fixations were recorded. In a third experiment, 14 participants drove a subset of the roads in a car while providing risk ratings at selected points of interest.

RESULTS showed a high degree of consistency across the different methods. Certain road situations were rated as being riskier than the objective risk, and perhaps more importantly, the risk of other situations was significantly under-rated. Horizontal curves and narrow lanes were associated with over-rated risk estimates, while intersections and roadside hazards such as narrow road shoulders, power poles and ditches were significantly under-rated. Analysis of eye movements indicated that drivers did not fixate these features and that the spread of fixations, pupil size and eye blinks were significantly correlated with the risk ratings. An analysis of the road design elements at 77 locations in the video revealed five road characteristics that predicted nearly 80% of the variance in drivers' risk perceptions; horizontal curvature, lane and shoulder width, gradient, and the presence of median barriers.