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Title:The Distracted Driver: Modeling the Impact of Information Bandwidth, in -Vehicle Task Priority, and Spatial -Separation on Driver Performance and Attention Allocation
Author(s):Horrey, William John
Doctoral Committee Chair(s):Wickens, Christopher D.
Department / Program:Psychology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Psychology, Experimental
Abstract:The introduction of new in-vehicle technologies (IVTs) and telematics into the automobile creates additional tasks that drivers may perform while driving. To the extent that these devices interfere with driving performance there will be concerns for safety. In three experiments, we explored how characteristics of the IVT task as well as the traffic environment impact driver performance and visual scanning behavior. For these experiments, younger drivers drove through varying traffic environments in a simulator while performing a concurrent number task presented on a visual IVT display. Experiment 1 examined the relative contribution of ambient vision to lane keeping performance with two different IVT displays locations (i.e., scans to the road were prohibited). We also examined the impact of increasing wind turbulence (bandwidth) on visual scanning behavior. Experiment 2a revisited the impact of bandwidth (for both wind turbulence and IVT information) and task priority (value) on performance and visual scanning. Experiment 2b explored how scanning effort and event salience impact the probability of fixating a given source of information. Experiment 3 reexamined the effects of wind bandwidth and increasing IVT task complexity on performance and visual scanning. We also introduced infrequent traffic hazard events that required an avoidance maneuver. Across all experiments, we did not find a strong influence of wind bandwidth on scanning behavior, suggesting that perhaps drivers are able to use ambient vision to support the driving task (Exp. 1), without necessarily requiring glances to the roadway. In contrast, task value had a significant impact on visual scanning (Exp. 2). Finally, we used a model of visual attention---the SEEV model (salience, effort, expectancy, and value)---to determine whether objective parameters of the driving environment and IVT task could predict differences in scanning behavior and whether these differences would or would not predict performance. Our modeling attempts did a good job of predicting actual scanning behavior, accounting for 92 to 97% of the variance across all experiments. For all tasks, the proportion of time spent looking at the area supporting the task was a good predictor of task performance (in terms of a performance-resource function).
Issue Date:2005
Description:151 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005.
Other Identifier(s):(MiAaPQ)AAI3199023
Date Available in IDEALS:2015-09-25
Date Deposited:2005

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