The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Teaming With a Synthetic Teammate: Insights into Human-Autonomy Teaming
Abstract
Objective: Three different team configurations are compared with the goal of better understanding human-autonomy teaming (HAT). Background: Although an extensive literature on human-automation interaction exists, much less is known about HAT in which humans and autonomous agents interact as coordinated units. Further research must be conducted to better understand how all-human teams compare to HAT. Methods: In an unmanned aerial system (UAS) context, a comparison was made among three types of three-member teams: (1) synthetic teams in which the pilot role is assigned to a synthetic teammate, (2) control teams in which the pilot was an inexperienced human, and (3) experimenter teams in which an experimenter served as an experienced pilot. Ten of each type of team participated. Measures of team performance, target processing efficiency, team situation awareness, and team verbal behaviors were analyzed. Results: Synthetic teams performed as well at the mission level as control (all human) teams but processed targets less efficiently. Experimenter teams performed better across all other measures compared to control and synthetic teams. Conclusion: Though there is potential for a synthetic agent to function as a full-fledged teammate, further advances in autonomy are needed to improve team-level dynamics in HAT teams. Application: This research contributes to our understanding of how to make autonomy a good team player.
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“Conversely, several mixed methods studies did meet our criteria and appear in the review (e.g., McNeese et al., 2018).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as McNeese et al., 2018
In the citing paper
“This is consistent with many descriptions of HATs in the literature (Demir, Cooke, et al., 2018; Demir, Likens, et al. 2018; Demir, McNeese, et al., 2018; Endsley, 2015; Fiore & Wiltshire, 2016; McNeese et al., 2018), but we formalize it here.”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as McNeese et al., 2018
In the citing paper
“Interdependence is relatively straightforward to identify, as it can be built into the task design and outcome distribution (e.g., McNeese et al., 2018, Nass et al., 1996; Walliser et al., 2019, 2019).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as McNeese et al., 2018
In the citing paper
“The CERTT-UAS-STE (Cooke & Shope, 2004) was a testbed used in 18 articles in our search (e.g., Demir, et al., 2016; Demir, Cooke, et al., 2018; Demir, Likens et al., 2018, Demir, McNeese, et al. 2018; McNeese et al., 2018).”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as McNeese et al., 2018
In the citing paper
“(I) Human–human teams generally had better outcomes than did HATs”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as McNeese et al. (2018)
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Guyton, Z., Pierson, K., Garay, T., Novitzky, M. M., McLaughlin, A. C., & Rovira, E. M. (2022) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181322661503
Examining the Effects of Cognitive Assistive Agents on Team Coordination in Manufacturing Teams
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Model-Based Architecture Tradeoff Analysis of Fighter-Drone Teaming System
Shi, W., & Chen, H. (2022) · IEEE International Conference on Unmanned Systems (ICUS) · doi:10.1109/icus55513.2022.9986784
Preliminary Insights into Enhancing Human-Robot Teamwork
Momose, K., Weekes, T. R., & Eskridge, T. C. (2023) · Florida Conference on Recent Advances in Robotics (FCRAR) · doi:10.5038/yexl3996
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Nols, T., Ulfert, A., & Gevers, J. (2024) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/ytced
Lyons, J. B., Sycara, K. P., Lewis, M., & Capiola, A. (2024) · Ingénierie cognitique · doi:10.21494/iste.op.2024.1132
O’Neill, T., Flathmann, C., McNeese, N. J., Jones, S. K., & Schelble, B. G. (2024) · Academy of Management Discoveries · doi:10.5465/amd.2024.0009
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Metadata
- Authors
- McNeese, N. J., Demir, M., Cooke, N. J., & Myers, C.
- Affiliations
- Clemson University (US)
- Arizona State University (US)
- United States Air Force Research Laboratory (US)
- Corresponding author
- McNeese, Nathan J.
- Venue
- Human Factors: The Journal of the Human Factors and Ergonomics Society
- Publisher
- SAGE Publications
- Published
- 2017-11-29
- Volume
- 60
- Issue
- 2
- Pages
- 262-273
- ISSN
- 0018-7208 (ISSN-L)
- 1547-8181
- OpenAlex
- W2770836081
- Cited by
- 380
- References
- 24
- Citations by year
- 2026: 66 · 2025: 74 · 2024: 60 · 2023: 52 · 2022: 44 · 2021: 35 · 2020: 26 · 2019: 15 · 2018: 6 · 2017: 1
- FWCI
- 17.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
- Locations
- Human Factors The Journal of the Human Factors and Ergonomics Society (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Office of Naval Research
- Topics
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- human-autonomy teaming, unmanned aerial systems, team performance, team situation awareness, human-automation interaction, team structure, pilot experience
- MeSH terms
- Pilots, Adult, Automation, Awareness, Cooperative Behavior, Humans, Man-Machine Systems, Psychomotor Performance, Verbal Behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
