Conference proceeding
Evaluating Human-automation Interaction Using Task Analytic Behavior Models, Strategic Knowledge-based Erroneous Human Behavior Generation, and Model Checking
2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), pp 1788-1794
01 Jan 2011
Abstract
Human-automation interaction, including erroneous human behavior, is a factor in the failure of complex, safetycritical systems. This paper presents a method for automatically generating task analytic models encompassing both erroneous and normative human behavior from normative task models by manipulating modeled strategic knowledge. Resulting models can be automatically translated into larger formal system models so that safety properties can be formally verified with a model checker. This allows analysts to prove that a human automationinteractive system (as represented by the formal model) will or will not satisfy safety properties with both normative and generated erroneous human behavior. This method is illustrated with a case study: the programming of a patient-controlled analgesia pump. In this example, a problem resulting from a generated erroneous human behavior is discovered and a potential solutions is explored. Future research directions are discussed.
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Details
- Title
- Evaluating Human-automation Interaction Using Task Analytic Behavior Models, Strategic Knowledge-based Erroneous Human Behavior Generation, and Model Checking
- Creators
- Matthew L. Bolton - Ames Research CenterEllen J. Bass - University of VirginiaIEEE
- Publication Details
- 2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), pp 1788-1794
- Series
- IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
- Publisher
- IEEE
- Number of pages
- 7
- Grant note
- NCCI002043 / NASA; National Aeronautics & Space Administration (NASA) T15LM009462 / National Library of Medicine (NLM); United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Library of Medicine (NLM)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000298615102013
- Scopus ID
- 2-s2.0-83755177715
- Other Identifier
- 991019292230204721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics
- Computer Science, Information Systems