The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Adaptive Automation for Human Supervision of Multiple Uninhabited Vehicles: Effects on Change Detection, Situation Awareness, and Mental Workload
Abstract
Human operators supervising multiple uninhabited air and ground vehicles (UAVs and UGVs) under high task load must be supported appropriately in context by automation. Two experiments examined the efficacy of such adaptive automation in a simulated high workload reconnaissance mission involving four subtasks: (a) UAV target identification; (b) UGV route planning; (c) communications, with embedded verbal situation awareness probes; and (d) change detection. The results of the first “baseline” experiment established the sensitivity of a change detection procedure to transient and nontransient events in a complex, multi-window, dynamic display. Experiment 1 also set appropriate levels of low and high task load for use in Experiment 2, in which three automation conditions were compared: manual; static automation, in which an automated target recognition (ATR) system was provided for the UAV task; and adaptive automation, in which individual operator change detection performance was assessed in real time and used to invoke the ATR if and only if change detection accuracy was below a threshold. Change detection accuracy and situation awareness were higher and workload was lower for both automation conditions compared to manual performance. In addition, these beneficial effects on change detection and workload were significantly greater for adaptive compared to static automation. The results point to the efficacy of adaptive automation for supporting the human operator tasked with supervision of multiple uninhabited vehicles under high workload conditions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research
(1988) · Advances in Psychology · doi:10.1016/s0166-4115(08)62386-9 · Cited by 15,003
Humans and automation: Use, misuse, disuse, abuse
Parasuraman, R., & Riley, V. (1997) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872097778543886 · Cited by 4,554
Self-citationA model for types and levels of human interaction with automation
Parasuraman, R., Sheridan, T. B., & Wickens, C. D. (2000) · IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans · doi:10.1109/3468.844354 · Cited by 4,195
Self-citationMeasurement of Situation Awareness in Dynamic Systems
Endsley, M. R. (1995) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872095779049499 · Cited by 2,039
Miller, C. A., & Parasuraman, R. (2007) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1518/001872007779598037 · Cited by 434
Self-citationPsychophysiology and adaptive automation
Byrne, E. A., & Parasuraman, R. (1996) · Biological Psychology · doi:10.1016/0301-0511(95)05161-9 · Cited by 360 · cited 1×
“For example, mental workload may be inferred from performance, physiological, or other measures (Byrne & Parasuraman, 1996; Kramer & Parasuraman, 2007; Wilson & Rus-sell, 2003).”
BackgroundSelf-citationadaptive aiding for human/computer control
Rouse, W. B. (1988) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/001872088803000405 · Cited by 252
Wiener, E. L. (1988) · Human Factors in Aviation · doi:10.1016/b978-0-08-057090-7.50019-9 · Cited by 174
Cited by
A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction
Hancock, P. A., Billings, D. R., Schaefer, K. E., Chen, J. Y. C., de Visser, E. J., & Parasuraman, R. (2011) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720811417254 · Cited by 2,051
Self-citationComplacency and Bias in Human Use of Automation: An Attentional Integration
Parasuraman, R., & Manzey, D. H. (2010) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720810376055 · Cited by 1,710
Self-citationAlmost human: Anthropomorphism increases trust resilience in cognitive agents.
de Visser, E. J., Monfort, S. S., McKendrick, R., Smith, M. A. B., McKnight, P. E., Krueger, F., & Parasuraman, R. (2016) · Journal of Experimental Psychology: Applied · doi:10.1037/xap0000092 · Cited by 614
Self-citationChong, L., Zhang, G., Goucher-Lambert, K., Kotovsky, K., & Cagan, J. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2021.107018 · Cited by 262
de Visser, E., & Parasuraman, R. (2011) · Journal of Cognitive Engineering and Decision Making · doi:10.1177/1555343411410160 · Cited by 207
Self-citation
Metadata
- Authors
- Parasuraman, R., Cosenzo, K. A., & De Visser, E.
- Venue
- Military Psychology
- Publisher
- Informa UK Limited
- Published
- 2009-03-31
- Volume
- 21
- Issue
- 2
- Pages
- 270-297
- ISSN
- 0899-5605 (ISSN-L)
- 1532-7876
- OpenAlex
- W2073515701
- Cited by
- 189
- References
- 8
- FWCI
- 18.54
- Type
- journal article
- Language
- en
- Open access
- closed
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.
