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Article type: Research Article
Authors: Khazab, M.a | Lo, S.b | Kilingaru, K.a | Tweedale, J.W.a; * | Jain, L.C.a | Thatcher, S.a | Ding, L.b
Affiliations: [a] School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Center, University of South Australia, Mawson Lakes, SA, Australia | [b] Faculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau SAR, China
Correspondence: [*] Corresponding author: J.W. Tweedale, School of Electrical and Information Engineering, Knowledge Based Intelligent Engineering Systems Center, University of South Australia, Mawson Lakes, SA, Australia. E-mail: jeffrey.tweedale@westnet.com.au
Abstract: This paper presents the outcomes of collaborative research between three PhD students working in the Multi-Agent System (MAS), Knowledge-Based System (KBS), and aviation Situation Awareness (SA) domains. The aim of this research was to create a MAS that could be used to monitor pilot SA during flight. SA is a cognitive activity that is a critical function conducted by pilots to maintain knowledge of their environment during flight. Good SA ultimately enhances the safety of passengers by reducing the possibility of pilots contributing to a number of documented catastrophic incidents. A controlled experiment has been devised to enable these students to capture and analyse pilot behaviour in an attempt to passively monitor SA monitoring activities using a camera. The MAS consists of multiple agent capabilities that capture the pilots visual acuity and eye movements. This data is used to assess the perceived cognitive activity in real-time. All agents can communicate and share the knowledge captured in order to analyse the activity based on pattern-matching rules using an embedded KBS. The experiments confirmed it is possible to identify at least three specific behaviours. The agents were able to post-process the acquired data to distinguish significant differences between an expert pilot and trained volunteers.
Keywords: Agents, multi-agent systems, knowledge-based system, agent communication languages, situation awareness, aviation safety
DOI: 10.3233/IDT-130166
Journal: Intelligent Decision Technologies, vol. 7, no. 4, pp. 237-251, 2013
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