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Massachusetts Institute of Technology

Modeling operator performance in low task load supervisory domains

Abstract

dc:description.abstract

Currently, numerous automated systems need constant monitoring but require little to no operator interaction for prolonged periods, such as unmanned aerial systems, nuclear power plants, and air traffic management systems. This combination can potentially lower operators' workload to dangerously low levels, causing boredom, lack of vigilance, fatigue, and performance decrements. As more systems are automated and placed under human supervision, this problem will become more prevalent in the future. To mitigate the problem through predicting operator performance in low task load supervisory domains, a queuing-based discrete event simulation model has been developed. To test the validity and robustness of this model, a testbed for single operator decentralized control of unmanned vehicles was utilized, simulating a low workload human supervisory control (HSC) environment. Using this testbed, operators engaged in a four-hour mission to search, track, and destroy simulated targets. Also, a design intervention in the form of cyclical auditory alerts was implemented to help operators sustain directed attention during low task load environments. The results indicate that the model is able to accurately predict operators' workload. Also, the model predicts operators' performance reasonably well. However, the inability of the model to account for operator error is a limiting factor that lowers model's accuracy. The results also show that the design intervention is not useful for operators who do not have difficulties sustaining attention for prolonged periods. The participants of this study were exceptional performers, since most of them had very high performance scores. Further research will investigate the possibility of conducting another low task load, long duration study with a more diverse set of participants to assess the impact of the design intervention and to extract personality traits that may affect system performance. Also, the model needs to be revised to take into account operator errors, which can significantly affect performance of HSC systems.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Mkrtchyan, Armen A
Advisor dc:contributor.advisor
  • Mary L. Cummings.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/67190
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/67190

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Mkrtchyan, Armen A. Modeling operator performance in low task load supervisory domains. Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/67190