The ability to detect hazards in video clips of driving has been inconsistently linked to driving experience and skill. One potential reason for the lack of consistency is the failure to understand the structural differences between those hazards that discriminate between safe and unsafe drivers, and those that do not. The current study used a car simulator to test drivers of differing levels of experience on approach to a series of hazards that were categorized a priori according to their underlying structure. The results showed that learner drivers took longer to fixate hazards, although they were particularly likely to miss hazards that were obscured by the environment (such as a pedestrian emerging from behind a parked truck). While drivers with a moderate amount of experience were as fast as driving instructors to look at hazards, they spent the greatest amount of time looking at them. Only instructors' ability to detect hazards early in the approach translated into differences in driving speed for certain types of hazard. The results demonstrate that drivers of varying experience respond differently to different hazards, and lay the foundations for a hazard typology.

What attracts attention when we inspect a scene? Two experiments recorded eye movements while viewers inspected pictures of natural office scenes in which two objects of interest were placed. One object had low contour density and uniform colouring (a piece of fruit), relative to another that was visually complex (for example, coffee mugs and commercial packages). In each picture the visually complex object had the highest visual saliency according to the Itti and Koch algorithm. Two experiments modified the task while the pictures were inspected, to determine whether visual saliency is invariably dominant in determining the pattern of fixations, or whether the purpose of inspection can provide a cognitive override that renders saliency secondary. In the first experiment viewers inspected the scene in preparation for a memory task, and the more complex objects were potent in attracting early fixations, in support of a saliency map model of scene inspection. In the second experiment viewers were set the task of detecting the presence of a low saliency target, and the effect of a high saliency distractor was negligible, supporting a model in which the saliency map can be built with cognitive influences that override low-level visual features.

No abstract

Our previous research has shown that observing patterns of eye fixations is a successful method of establishing differences in underlying cognitive processes between groups of drivers. Eye movements recorded from drivers in a laboratory while they watch film clips recorded from a driver's perspective can be used to identify scanpaths and search patterns that reveal ability differences. In the present study 12 older subjects (60-75 years) and 12 younger subjects (30-45 years) watched clips for potential hazards such as other road users appearing on an intersecting trajectory. Acuity and visual field differences between the two groups were eliminated through screening, so that only age-related differences would emerge. Eye fixations were analysed on a frame-by-frame basis to generate sequences of codes representing the location and object of the viewer's interest, before and during the appearance of a hazard. These codes were analysed for the existence of two fixation scanpaths using Markov Matrices. Unique scanpaths were identified for each group of drivers before and during the hazard. Evidence from the inspection of different objects and from the spread of the search indicated that both groups of driver were sensitive to attentional capture by the appearance of the hazard. Detection of the hazards - both speed and accuracy - was similar for older and younger drivers, although the older drivers perceived the films as being more hazardous in general. There is little evidence in this study of an age-related decline in the search of the scene when detecting hazards.

This study investigated whether individuals with ASD (autistic spectrum disorders) are able to identify driving hazards, given their difficulties processing social information, Klin et al. (Archives of General Psychiatry 59: 809-816, 2002). Twenty-three adult males with ASD and 21 comparison participants viewed 10 video clips containing driving hazards. In half of the clips the source of the hazard was a visible person (social); in the other half the source was a car (non-social). Participants with ASD identified fewer social hazards than the comparison participants (U = 163.00, N = 44, p < .05) but not non-social. Participants with ASD were also slower to respond than comparison participants, F(1,40) = 4.93, p < .05. This suggests that, although people with ASD can perceive driving hazards they may have specific difficulty identifying them if they involve a person.