

Type of Document Master's Thesis Author Wojciechowski, Josephine Quinn Author's Email Address jqw@arl.army.mil URN etd-04142006-133043 Title Validation of a Task Network Human Performance Model of Driving Degree Master of Science Department Industrial and Systems Engineering Advisory Committee
Advisor Name Title Kleiner, Brian M. Committee Chair Babski-Reeves, Kari L. Committee Member Hill, Susan Committee Member Keywords
- workload
- driving
- distractions
- human performance modeling
- IMPRINT
Date of Defense 2006-04-05 Availability unrestricted Abstract Human performance modeling (HPM) is often used to investigate systems during all phases of development. HPM was used to investigate function allocation in crews for future combat vehicles. The tasks required by the operators centered around three primary functions, commanding, gunning, and driving. In initial investigations, the driver appeared to be the crew member with the highest workload.Validation of the driver workload model (DWM) is necessary for confidence in the ability of the model to predict workload. Validation would provide mathematical proof that workload of driving is high and that additional tasks impact the performance.
This study consisted of two experiments. The purpose of each experiment was to measure performance and workload while driving and attending to an auditory secondary task. The first experiment was performed with a human performance model. The second experiment replicated the same conditions in a human-in-the-loop driving simulator. The results of the two experiments were then correlated to determine if the model could predict performance and workload changes.
The results of the investigation indicate that there is some impact of an auditory task on driving. The model is a good predictor of mental workload changes with auditory secondary tasks. However, predictions of the impact on performance from secondary auditory tasks were not demonstrated in the simulator study. Frequency of the distraction was more influential in the changes of performance and workload than the demand of the distraction, at least under the conditions tested in this study. While the workload numbers correlate with simulator numbers, using the model would require a better understanding of what the workload changes would mean in terms of performance measures.
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