A socio-technical holistic agent based model to assess cockpit supporting tools performance variability

Piera, Miquel Àngel; Ramos, Juan José; Muñoz, José Luis Jurado

doi:10.1016/j.ifacol.2019.09.128

IFAC-PapersOnLine

2019

DOI: 10.1016/j.ifacol.2019.09.128

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A socio-technical holistic agent based model to assess cockpit supporting tools performance variability

Miquel Àngel Piera

Juan José Ramos

José Luis Jurado Muñoz³

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2022

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Cited by 2 publications

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“…The functional resonance analysis method (FRAM) [39] is an agent based modeling framework to identify those factors that affect the performance of the pilot in cockpit functionalities considering different socio-technical operational conditions. According to this agent, the impact of an interruption on the PF workflow depends largely on the time at which the interruption occurs.…”

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confidence: 99%

Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals

et al. 2022

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The commercial flightdeck is a naturally multi-tasking work environment, one in which interruptions are frequent come in various forms, contributing in many cases to aviation incident reports. Automatic characterization of pilots’ workloads is essential to preventing these kind of incidents. In addition, minimizing the physiological sensor network as much as possible remains both a challenge and a requirement. Electroencephalogram (EEG) signals have shown high correlations with specific cognitive and mental states, such as workload. However, there is not enough evidence in the literature to validate how well models generalize in cases of new subjects performing tasks with workloads similar to the ones included during the model’s training. In this paper, we propose a convolutional neural network to classify EEG features across different mental workloads in a continuous performance task test that partly measures working memory and working memory capacity. Our model is valid at the general population level and it is able to transfer task learning to pilot mental workload recognition in a simulated operational environment.

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confidence: 99%

Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals

et al. 2022

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A reinforcement learning development of the FRAM for functional reward-based assessments of complex systems performance

Salehi

Tran

Veitch

et al. 2022

International Journal of Industrial Ergonomics

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A socio-technical holistic agent based model to assess cockpit supporting tools performance variability

Cited by 2 publications

References 9 publications

Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals

Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals

A reinforcement learning development of the FRAM for functional reward-based assessments of complex systems performance

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