Automation has been introduced more and more into the role of air traffic control (ATC). As with many other areas of human activity, automation has the objective of reducing the complexity of the task so that performance is optimised and safer. However, automation can also have negative effects on cognitive processing and the performance of the controllers. In this paper, we present the progress made at AUTOPACE, a European project in which research is carried out to discover what these negative effects are and to propose measures to mitigate them. The fundamental proposal of the project is to analyse, predict, and mitigate these negative effects by assessing the complexity of ATC in relation to the mental workload experienced by the controller. Hence, a highly complex situation will be one with a high mental workload and a low complex situation will be one in which the mental workload is low.

Mental Workload in the Explanation of Automation Effects on ATC Performance / José Juan Cañas1, Pedro Ferreira, Patricia López de Frutos, Eva Puntero, Elena López, Fernando Gómez-Comendador, Francesca de Crescenzio, Francesca Lucchi, Fedja Netjasov, and Bojana Mirkovic. - STAMPA. - 1012:(2019), pp. 202-221. (Intervento presentato al convegno H-WORKLOAD 2018 tenutosi a Amsterdam, the Netherlands nel September 2018) [10.1007/978-3-030-14273-5_12].

Mental Workload in the Explanation of Automation Effects on ATC Performance

Francesca de Crescenzio;Francesca Lucchi;
2019

Abstract

Automation has been introduced more and more into the role of air traffic control (ATC). As with many other areas of human activity, automation has the objective of reducing the complexity of the task so that performance is optimised and safer. However, automation can also have negative effects on cognitive processing and the performance of the controllers. In this paper, we present the progress made at AUTOPACE, a European project in which research is carried out to discover what these negative effects are and to propose measures to mitigate them. The fundamental proposal of the project is to analyse, predict, and mitigate these negative effects by assessing the complexity of ATC in relation to the mental workload experienced by the controller. Hence, a highly complex situation will be one with a high mental workload and a low complex situation will be one in which the mental workload is low.
2019
Human Mental Workload: Models and Applications. H-WORKLOAD 2018. Communications in Computer and Information Science
202
221
Mental Workload in the Explanation of Automation Effects on ATC Performance / José Juan Cañas1, Pedro Ferreira, Patricia López de Frutos, Eva Puntero, Elena López, Fernando Gómez-Comendador, Francesca de Crescenzio, Francesca Lucchi, Fedja Netjasov, and Bojana Mirkovic. - STAMPA. - 1012:(2019), pp. 202-221. (Intervento presentato al convegno H-WORKLOAD 2018 tenutosi a Amsterdam, the Netherlands nel September 2018) [10.1007/978-3-030-14273-5_12].
José Juan Cañas1, Pedro Ferreira, Patricia López de Frutos, Eva Puntero, Elena López, Fernando Gómez-Comendador, Francesca de Crescenzio, Francesca Lucchi, Fedja Netjasov, and Bojana Mirkovic
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/679608
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