Title: Individual performance markers and working memory predict supervisory control proficiency and effective use of adaptive automation
Authors: Haneen Saqer; Raja Parasuraman
Addresses: Department of Psychology, Human Factors & Applied Cognition, George Mason University, MSN 3F5, 4400 University Drive, Fairfax, VA 22030-4444, USA ' Center of Excellence in Neuroergonomics, Technology and Cognition (CENTEC); Department of Psychology, Human Factors & Applied Cognition, George Mason University, MSN 3F5, 4400 University Drive, Fairfax, VA 22030-4444, USA
Abstract: Adapting automation to transient operator states and changes in the environment has been shown to be more effective than static automation. Adaptive automation design that incorporates individual human operator differences can further enhance human-automation interaction. In this study participants performed a simulated air defence task under low and high task load and three levels of automation (manual, low and high). Automated aids autonomously engaged targets and communicated actions via a text messaging system. Baseline performance measures not only predicted future performance but also predicted use of automation. Operators with high skill proficiency exhibited greater disuse of automation compared to their lower skill counterparts. Contrary to previous findings, working memory spans did not predict overall performance, but did predict appropriate use of automation in non-context matched scenarios. When automation was not matched to level of task load, operators with higher spans were better able to coordinate with automation than lower span individuals.
Keywords: adaptive automation; individual differences; supervisory control; unmanned vehicles; UVs; working memory capacity; individual performance markers; human-automation interaction; simulation; air defence tasks; text messaging; performance measures; skills proficiency; automation usage levels.
International Journal of Human Factors and Ergonomics, 2014 Vol.3 No.1, pp.15 - 31
Received: 13 Dec 2013
Accepted: 20 Feb 2014
Published online: 06 Jun 2014 *