Abstract
The paper describes an approach to modeling the strategic variations in performing secondary tasks while driving. In contrast to previous efforts that are based on simulation of a cognitive architecture interacting with a task environment, we take an approach that develops a cognitive constraint model of the interaction between the driver and the task environment in order to make inferences about dual-task performance. Analyses of driving performance data reveal that a set of simple equations can be used to accurately model changes in the lateral position of the vehicle within the lane. The model quantifies how the vehicle's deviation from lane center increases during periods of inattention, and how the vehicle returns to lane center during periods of active steering. We demonstrate the benefits of the approach by modeling the dialing of a cellular phone while driving, where drivers balance the speed in performing the dial task with accuracy (or safety) in keeping the vehicle centered in the roadway. In particular, we show how understanding, rather than simulating, the constraints imposed by the task environment can help to explain the costs and benefits of a range of strategies for interleaving dialing and steering. We show how particular strategies are sensitive to a combination of internal constraints (including switch costs) and the trade-off between the amount of time allocated to secondary task and the risk of extreme lane deviation. © Copyright 2007 ACM.
Original language | English |
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Title of host publication | Conference on Human Factors in Computing Systems - Proceedings|Conf Hum Fact Comput Syst Proc |
Pages | 233-242 |
Number of pages | 9 |
Publication status | Published - 2007 |
Event | 25th SIGCHI Conference on Human Factors in Computing Systems 2007, CHI 2007 - San Jose, CA Duration: 1 Jul 2007 → … |
Conference
Conference | 25th SIGCHI Conference on Human Factors in Computing Systems 2007, CHI 2007 |
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City | San Jose, CA |
Period | 1/07/07 → … |
Keywords
- Driver distraction
- Multitasking
- User modeling