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Designing and Training for Appropriate Trust in Increasingly Autonomous Advanced Air
Mobility Operations: A Mental Model Approach: Version 1
To enable effective human-autonomy teaming (HAT) in Advanced Air Mobility (AAM) operations, the current paper presents a theoretical framework to design and train for appropriate trust in automation. The novel contribution of this work resides in connecting the construct of trust to mental models and showing how this method could be used to enable emerging HAT concepts such as Adaptive Trust Calibration. To contextualize this framework, in section 2 we discuss simplified vehicle operations (SVO) and remote vehicle operations (RVO), which are leading operational concepts within AAM. In section 3 we describe our perspective on automation and increasingly autonomous systems and present a brief discussion on human-automation interaction and human-autonomy teaming. In section 4 we
provide a detailed discussion on the construct of trust in automation. In section 5 we present a framework that associates mental models with trust through principles of transparent design. Finally, in section 6 we present three descriptive models for designing and training for appropriate trust in increasingly autonomous systems.
Document ID
Acquisition Source
Langley Research Center
Document Type
Technical Memorandum (TM)
Eric T Chancey
(Langley Research Center Hampton, Virginia, United States)
Mike Politowicz
(Langley Research Center Hampton, Virginia, United States)
Date Acquired
June 9, 2020
Publication Date
December 1, 2020
Subject Category
Behavioral Sciences
Air Transportation And Safety
Funding Number(s)
WBS: 109492.
Distribution Limits
Public Use Permitted.
Human-Autonomy Teaming
Mental Models
Advanced Aerial Mobility
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