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IMPRINT Workload Modeling: FY04 and FY05 Work

IMPRINT Workload Modeling: FY04 and FY05 Work. Raja Parasuraman Cognitive Science Laboratory George Mason University. Tasks—FY04. Review Existing Task Scheduling and Workload Modeling Theory and Research Evaluate Workload Management Strategies in IMPRINT

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IMPRINT Workload Modeling: FY04 and FY05 Work

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  1. IMPRINT Workload Modeling: FY04 and FY05 Work Raja Parasuraman Cognitive Science Laboratory George Mason University

  2. Tasks—FY04 • Review Existing Task Scheduling and Workload Modeling Theory and Research • Evaluate Workload Management Strategies in IMPRINT • Identify and Define Proposed Modifications

  3. Overview and Scope • Outline theoretical foundations for enhancing IMPRINT capabilities in two areas: • Workload modeling • Workload management strategies • Focus on theory, not on IMPRINT tools and models

  4. Overview and Scope (contd.) • Took a “blue sky” approach--considered all possible potential enhancements based on current workload research • Starting points • Mitchell (2000) ARL Technical Report • Wickens (2002) TIES journal article

  5. Descriptors • Theoretical foundation • Implications for IMPRINT • “Seat of the pants” evaluation

  6. Potential Enhancements in Workload Modeling • Updated Implementation of Multiple Resource Theory: Focal vs. Ambient Vision • Cross-Modal Links in Spatial Attention • Time and Intensity Based Models (Hendy’s IP/PCT Model) • MART: Malleable Attentional Resource Theory • Dynamic Workload Modeling • Task Prioritization • Concurrent Task Management (CTM) • Latent Performance Decrements • Task Shifting

  7. Example 1: Cross-Modal Links in Attention • Theoretical Foundation: Although different sensory modalities generally define different resource pools, cross-modal links are present, particularly as a function of common spatial location (Spence & Read, 2003) • Implications for IMPRINT: Revision of workload model, in particular the sensory modality resource type, and the resulting conflict matrix • Initial Evaluation: Implement, given strong background evidence for importance of cross-modal links in spatial attention

  8. Example 2: Time and Intensity Based Models Model (Hendy’s IP/PCT) • Theoretical Foundation: Time to perform a task as a function of time available can be used to predict overall workload, whereas intensity of processing has a lesser effect • Implications for IMPRINT: Revision of workload model, eliminating resource demand and conflict matrix and replacing with a percentage time metric • Initial Evaluation: Do not implement, given that percentage time metrics cannot account for lack of interference from time consuming but minimally resource demanding tasks. Using resource demands and the conflict matrix gives a designer better, more concrete, recommendations pertinent to workstation redesign and therefore more valuable than time-based methods

  9. Tasks—FY05 • Re-examine the mental workload scales in IMPRINT and split the visual workload scale into ambient and focal scales • Benchmark values against verbal descriptors and recommend default values for the resource pair conflict matrix.

  10. Visual Workload • Visual workload is influenced by numerous task, operator, and environmental factors • Current IMPRINT workload algorithm includes a number of these factors • However, current workload algorithm does not distinguish between focal and ambient visual workload

  11. Focal and Ambient Vision • Focal vision: Visual tasks requiring the interpretation of detail (e.g., reading text) • Ambient vision: Visual tasks involving self motion and detection of moving objects (e.g., driving, walking)

  12. Focal and Ambient Taxons

  13. Focal Vision Descriptors Scale ValueVisual Scale Descriptor 0.0 No Visual Activity 1.0 Visually Register/Detect (detect occurrence of image) 3.7 Visually Discriminate (detect visual differences) 4.0 Visually Inspect/Check (discrete inspection/static condition) 4.5 Visually inspect multiple displays separated by less than 20o 5.9 Visually Read (symbol) 6.0 Visually inspect/read in low luminance conditions 6.2 Visually inspect multiple displays separated by more than 20o 7.0 Visually scan/search/monitor (continuous/serial inspection, multiple conditions)

  14. Ambient Vision Descriptors Scale ValueVisual Scale Descriptor 0.0 No visual Activity 1.0 Visually monitor for headway maintenance at speeds below 8 mph 1.5 Visually monitor for headway maintenance at speeds above 10 mph 2.7 Visually process/regulate speed of motion 3.7 Visually monitor optic flow when field of view (FOV) is restricted to less than 90o 4.0 Visually locate/align (selective orientation) 5.4 Maintain orientation (i.e., pitch, roll, yaw) during visual tracking/following 6.0 Visually scan/search/monitor (continuous/vigilant monitoring in peripheral vision – high luminance conditions)

  15. Focal-Ambient Channel Conflict Matrix

  16. Additional Visual Workload Distinctions • Distinguish between focal-verbal, focal-spatial, ambient-verbal, and ambient-spatial processes • Distinguish peripersonal (reaching, grasping, and manipulating objects) and extrapersonal spae (activation of attentional, memory and voluntary motor systems).

  17. Potential Enhancements in Workload Modeling • Updated Implementation of Multiple Resource Theory: Focal vs. Ambient Vision • Cross-Modal Links in Spatial Attention • Time and Intensity Based Models (Hendy’s IP/PCT Model) • MART: Malleable Attentional Resource Theory • Dynamic Workload Modeling • Task Prioritization • Concurrent Task Management (CTM) • Latent Performance Decrements • Task Shifting

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