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Wetware, Hardware, or Software Incapacitation: Observational Methods to Determine When Autonomy Should Assume Control
Author(s) -
Anna Trujillo,
Irene M. Gregory
Publication year - 2014
Publication title -
14th aiaa aviation technology, integration, and operations conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2014-2704
Subject(s) - workload , computer science , identification (biology) , software , criticality , control (management) , operator (biology) , causality (physics) , work (physics) , simulation , engineering , artificial intelligence , operating system , mechanical engineering , biochemistry , chemistry , botany , physics , repressor , quantum mechanics , nuclear physics , transcription factor , gene , biology , programming language
Control-theoretic modeling of human operator's dynamic behavior in manual control tasks has a long, rich history. There has been significant work on techniques used to identify the pilot model of a given structure. This research attempts to go beyond pilot identification based on experimental data to develop a predictor of pilot behavior. Two methods for pre-dicting pilot stick input during changing aircraft dynamics and deducing changes in pilot behavior are presented This approach may also have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot. With this ability to detect changes in piloting behavior, the possibility now exists to mediate human adverse behaviors, hardware failures, and software anomalies with autono-my that may ameliorate these undesirable effects. However, appropriate timing of when au-tonomy should assume control is dependent on criticality of actions to safety, sensitivity of methods to accurately detect these adverse changes, and effects of changes in levels of auto-mation of the system as a whole.

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