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S. A. Metalis

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Publications by S. A. Metalis (bibliography)

1995

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Metalis, S. A., Pennella, R. N. and Rodriguez, S. L. (1995): Stick Control Modulations Index Pilot Mental Workload. In: Proceedings of the Human Factors and Ergonomics Society 39th Annual Meeting 1995. p. 952.

“A single subject repeated measures design, replicated four times, was used to investigate the utility of stick control modulations to index pilot workload. Four subjects engaged in an aircraft-type workload simulation task. Our modification of the Multi-Attribute Task Battery consisted of a primary task (a video-game-like stick control task, wherein the goal is to place crosshairs over an evasive target aircraft symbol), and a secondary task, (accuracy/time-to-respond to out-of-normal range cues to gauges and warning lights). The subject simultaneously performed the primary and secondary task on even numbered game trials; on odd numbered trials only the primary task was performed. On a relative scale the first two games were slow, the next two were medium, and the last two were fast. The three levels of workload due to gamespeed and two levels due to primary/secondary tasks comprised a six-game set. A subject's data from twenty such sets were analyzed in a 3 * 2 factorial design. For each 30-sec. game the dependent measures consisted of a set of three workload criterion variables, including global subjective workload ratings, accuracy scores (a function of time on target), and tracking RMS error; a set of eight statistics on stick modulations, including mean amplitude, velocity, acceleration, frequency, as well as amplitude SD, velocity SD, amplitude skew, and velocity skew; and a set of four power spectrum array (PSA) data from the x- and y- axis waveforms characterizing stick modulations, including energy in four bandwidths: .1 to .3 Hz, .3 to .6 Hz, .6 to 1.0 Hz, and 1.0 to 1.3 Hz. Findings indicate that the three criterion variables differed as a function of the two workload manipulations. But the stick statistics and the PSA data did not index the two workload dimensions equally well. All the dependent measures were influenced by the gamespeed dimension, whereas only the PSA at the .1 to .3 Hz band was influenced by the primary/secondary workload dimension. This evidence suggests that measures of stick modulations can help characterize pilot workload.”

1993

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Metalis, S. A. (1993): Assessment of Pilot Situational Awareness: Measurement via Simulation. In: Proceedings of the Human Factors and Ergonomics Society 37th Annual Meeting 1993. pp. 113-117.

“While pilots have an intuitive understanding of situational awareness (SA), researchers have had difficulty defining and measuring SA for practical ends such as pilot selection, training and cockpit design evaluation. To achieve the latter end a model of SA is proposed and a measurement technique is described. Specifically, SA appears to involve the development and maintenance of a highly dynamic mental representation of critical aspects of the flying environment. Using this system the pilot makes judicious decisions in a timely manner with little conscious effort. To render SA measurable, SA may be modeled as a computer system with elements and processes which serve to develop and maintain an extremely fast, efficient database. Computer systems are assessed via benchmark tests. To measure SA, the pilot flies a benchmark test which consists of a standardized mission in a medium fidelity simulator under progressively increasing assigned airspeeds. The pilot's SA is measured via techniques including objective metrics such as flying performance and responses to "unexpected" events, as well as subjective metrics such as ratings and knowledge elicitation. All must of necessity be indirect measures of SA for the pilot's actions reflect not only SA but the adequacy of the data initially available as well as the quality of training, talent, and the vehicle itself. A statistically weighted combination of these measures is used in order to improve sensitivity and minimize their individual limitations.”

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