The Attentional Demand of Automobile Driving Revisited: Occlusion Distance as a Function of Task-Relevant Event Density in Realistic Driving Scenarios
Abstract
Objective:
We studied the utility of occlusion distance as a function of task-relevant event density in realistic traffic scenarios with self-controlled speed.
Background:
The visual occlusion technique is an established method for assessing visual demands of driving. However, occlusion time is not a highly informative measure of environmental task-relevant event density in self-paced driving scenarios because it partials out the effects of changes in driving speed.
Method:
Self-determined occlusion times and distances of 97 drivers with varying backgrounds were analyzed in driving scenarios simulating real Finnish suburban and highway traffic environments with self-determined vehicle speed.
Results:
Occlusion distances varied systematically with the expected environmental demands of the manipulated driving scenarios whereas the distributions of occlusion times remained more static across the scenarios. Systematic individual differences in the preferred occlusion distances were observed. More experienced drivers achieved better lane-keeping accuracy than inexperienced drivers with similar occlusion distances; however, driving experience was unexpectedly not a major factor for the preferred occlusion distances.
Conclusion:
Occlusion distance seems to be an informative measure for assessing task-relevant event density in realistic traffic scenarios with self-controlled speed. Occlusion time measures the visual demand of driving as the task-relevant event rate in time intervals, whereas occlusion distance measures the experienced task-relevant event density in distance intervals.
Application:
The findings can be utilized in context-aware distraction mitigation systems, human–automated vehicle interaction, road speed prediction and design, as well as in the testing of visual in-vehicle tasks for inappropriate in-vehicle glancing behaviors in any dynamic traffic scenario for which appropriate individual occlusion distances can be defined.
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Biographies
Tuomo Kujala is a postdoctoral researcher in the Department of Computer Science and Information Technology in the University of Jyväskylä. He earned his PhD degree in cognitive science from the University of Jyväskylä, Finland in 2010.
Jakke Mäkelä earned his PhLic degree in theoretical physics in 1998 and PhD in physics in 2010, both from the University of Helsinki, Finland. He is a project researcher in the Department of Computer Science and Information Technology in the University of Jyväskylä.
Ilkka Kotilainen is a research assistant in the Department of Computer Science and Information Technology in the University of Jyväskylä and an intern in the Finnish Transport Agency. He earned his master’s degree in economics in 2014.
Timo Tokkonen is a project manager at the University of Jyväskylä. He has over 20 years of executive and domain experience in building and using novel high-tech solutions in astronomy, mobile telecommunications, and various fields of industry including automotive.
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Article first published online: August 3, 2015
Issue published: February 2016
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PubMed: 26238120
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