Compensating for failed attention while driving |
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Affiliation: | 1. Louisiana State University, USA;2. Gulf Coast Center for Evacuation and Transportation Resiliency, USA;1. Centre for Computational Neuroscience and Cognitive Robotics, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK;2. Behavioural Brain Sciences, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK;1. Department of Psychology, NUI Maynooth, Co. Kildare, Ireland;2. Department of Engineering, IT Blanchardstown, Dublin, Ireland;3. Department of Computer Science, NUI Maynooth, Co. Kildare, Ireland |
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Abstract: | While operating a motor vehicle, drivers must pay attention to other moving vehicles and the roadside environment in order to detect and process critical information related to the driving task. Using a driving simulator, this study investigated the effects of an unexpected event on driver performance in environments of more or less clutter and under situations of high attentional load. Attentional load was manipulated by varying the number of neighboring vehicles participants tracked for lane changes. After baseline-driving behavior was established, the unexpected event occurred: a pedestrian ran into the driver’s path. Tracking-accuracy, brake initiation, swerving, and verbal report of the unexpected pedestrian were used to assess driver performance. All participants verbally reported noticing the pedestrian. However, analyses of driving behavior revealed differences in the reactions to the pedestrian: drivers braked faster and had significantly less deviation in their steering heading with a lower attentional load, and participants in low clutter environments had a larger overall change in velocity. This research advances the understanding of how drivers allocate attention between various stimuli and the trade-offs between a driver’s focus on an assigned task and external objects within the roadway environment. Moreover, the results of this research lend insight into how to construct roadway environments that encourage driver attention toward the most immediate and relevant information to reduce both vehicle-to-vehicle and vehicle-to-pedestrian interactions. |
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Keywords: | Attention Driving Simulation Distraction Compensation |
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