1 / 13

ONR Principle Investigators: Dr. Joe DiVita, Code 244209 joseph.divita@navy.mil

Modeling of Human-Computer Interaction: Application to Command & Control. Presented at Systems Design Technical Group Meeting HFS Annual Conference, Denver Colorado, Oct. 2003. ONR Principle Investigators: Dr. Joe DiVita, Code 244209 joseph.divita@navy.mil

phong
Download Presentation

ONR Principle Investigators: Dr. Joe DiVita, Code 244209 joseph.divita@navy.mil

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Modeling of Human-Computer Interaction: Application to Command & Control Presented at Systems Design Technical Group Meeting HFS Annual Conference, Denver Colorado, Oct. 2003 ONR Principle Investigators: Dr. Joe DiVita, Code 244209 joseph.divita@navy.mil Dr Glenn Osga, Code 2441 glenn.osga@navy.mil Dr. David Kieras - University of Michigan Dr. Tom Santoro - NSMRL Groton CT Mr. Rob Morris, Code 244209 rob.morris@navy.mil Contributors: Dr. Hung T. Nguyen- New Mexico State University

  2. GOMS Components Goals:What Must be Accomplished Operators:Elementary Perceptual, Motor, or Cognitive Acts. Methods:Step by Step Procedure for a Goal Selection Rules: Basis for Choosing Methods Based upon Stepwise models as defined in: Psychology of Human-Computer Interaction, Card, Moran, and Newell (1983).

  3. GLEAN: GOMS Language Evaluation and Analysis Tool Simulated Interaction Devices Auditory Input Cognitive Processor Auditory Processor Task Environment Visual Input Visual Processor Vocal Motor Processor GOMS Language Interpreter Manual Motor Processor Working Memory Declarative and Procedural Knowledge in Long Term memory Model-based Evaluation David Kieras University of Michigan to appear in J. Jacko & A. Sears (Eds), Human-Computer Interaction Handbook, Lawrence Erlbaum Associates, in press

  4. Using Models for Design Trade-Off Studies Analysis Procedure: 1. Task Analysis • Define the Goals: • How are they accomplished ? • How might they be accomplished? • What are the alternatives? • 2. Write the Methods in GOMSL, • 3. Build the HCI and Task Environment in C++, • 4. Run the Scenario(s) & Review Results.

  5. Display Design Components

  6. Task Manager & Status Display Task Manager Task Queue Systems Status Communications

  7. Process Visualization - Tactical Tomahawk Strike Plan Overview Task Progress

  8. Comparison Results Avg Time Avg Time Method for Goal Frequency Frequency SPOKEN SYNTHETIC SPOKEN SYNTHETIC 28.445 20.418 Respond_to New_Air 76 76 22.248 16.662 Update_Air Trk 168 242 7.355 7.344 Review Air_ID 244 318 2.208 2.727 Review Track_profile 124 160 4.598 5.402 Conduct Threat_Assessment 124 160 14.228 14.285 Request Escort 9 10 15.150 12.675 Request Visual ID 2 8 14.790 3.491 Issue Query 10 19 16.075 4.644 Issue Warning 12 18 14.545 3.500 New_Track_Verbal_Rpt 76 76 14.427 3.536 Update_Track_Verbal_Rpt 74 105 2.015 2.094 Hook Track 244 318

  9. Example: New Track Report Task Flow Actual Team Results GOMSL Model Results GOMSL Model with fast working memory Text to Speech completed Task arrives on TM display AWC operator selects task AWC operator sends report Mean Waiting time in the queue Team 1 data = 51.2 s GOMSL Model = 55.2s Mean time = 10.1 s Mean Service Time Team 1 data = 6.7 s GOMSL Model = 10.3 s GOMSL Model = 5.5 s GOMSL Model = 9.43 GOMSL Model = 9.10 GOMSL Model = 52.26 AWC receives acknowledgment

  10. Network Queueing Model of Team 1 Task Flow. Level I & II’s Level I* & II*, ordered to send. IQC1 Operator Tasks Entering: New track Report Update track Report Level 1Query Level II Warn VID Cover Engage Illuminate Tasks performed - Output flow AWC Operator VID AIC Operator Tasks performed - Output Flow

  11. i = • i + • j pji • i • i= • i • i = rate of incoming tasks N= • i /( • i /( • i - • i) • i) T= • i - • i 1 P( • (1- • ) = • i) • ini General Open Network Queueing Model Network Stats: • 2 incoming tasks Load to each node: • i= the effective arrival rate to node i. pji=probability that a task, after receiving service by node j, proceeds to node i. IQC1 • 2 Ave #, N, of tasks in the whole system: Tasks passed between operators • 1 incoming tasks AWC Ave time, T, of tasks in the system: AIC • 3 • i= service time of task Probability of a particular state (n1, n2, n3) tasks: • 1 • 3 incoming tasks

  12. Team 2 takes 36% longer to complete New Track Reports

  13. Modeling Plans • Expand Models • Basic models constructed for Air Defense mission and Land Attack with Tomahawk. • Models based upon future HCI designs being incorporated into Tomahawk. • Expand individual models into tactical team models. • Design Feedback • Provide design feedback on best features to improve performance. • Team Design • Compare team work allocation, flow, process with various team configurations for future systems.

More Related