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.
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Citations
Cites
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BackgroundSelf-citationadaptive aiding for human/computer control
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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-citationInsights into Human-Agent Teaming: Intelligent Agent Transparency and Uncertainty
Stowers, K., Kasdaglis, N., Rupp, M., Chen, J., Barber, D., & Barnes, M. (2017) · Advances in Intelligent Systems and Computing · doi:10.1007/978-3-319-41959-6_13 · Cited by 28
Evaluation of a Decision-Based Invocation Strategy for Adaptive Support for Air Traffic Control
IJtsma, M., Borst, C., van Paassen, M. M., & Mulder, M. (2022) · IEEE Transactions on Human-Machine Systems · doi:10.1109/thms.2022.3208817 · Cited by 13
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
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