Sleep loss and change detection in driving scenes
journal contributionposted on 09.02.2018 by Ashleigh Filtness, Vanessa Beanland
Any type of content formally published in an academic journal, usually following a peer-review process.
© 2017 Elsevier Ltd. Driver sleepiness is a significant road safety problem. Sleep-related crashes occur on both urban and rural roads, yet to date driver-sleepiness research has focused on understanding impairment in rural and motorway driving. The ability to detect changes is an attention and awareness skill vital for everyday safe driving. Previous research has demonstrated that person states, such as age or motivation, influence susceptibility to change blindness (i.e., failure or delay in detecting changes). The current work considers whether sleepiness increases the likelihood of change blindness within urban and rural driving contexts. Twenty fully-licenced drivers completed a change detection 'flicker' task twice in a counterbalanced design: once following a normal night of sleep (7-8 h) and once following sleep restriction (5 h). Change detection accuracy and response time were recorded while eye movements were continuously tracked. Accuracy was not significantly affected by sleep loss; however, following sleep loss there was some evidence of slowed change detection responses to urban images, but faster responses for rural images. Visual scanning across the images remained consistent between sleep conditions, resulting in no difference in the probability of fixating on the change target. Overall, the results suggest that sleep loss has minimal impact on change detection accuracy and visual scanning for changes in driving scenes. However, a subtle difference in response time to change detection between urban and rural images indicates that change blindness may have implications for sleep-related crashes in more visually complex urban environments. Further research is needed to confirm this finding.
This work was supported by an NRMA-ACT Road Safety Trust Grant. Vanessa Beanland is supported by an Australian Research Council Discovery Early Career Researcher Award [grant DE150100083].