Portal de Conferências da UFSC, XX Sitraer

Tamanho da fonte: 
ANDERSON DE MATOS CASTRO, Michelle Carvalho Galvão da Silva Pinto Bandeira

Última alteração: 2023-09-26


The development of the first autopilots in the 1930s can be considered the first step towards automation in airplanes. Various industries experienced significant transformations, especially the commercial aviation sector through technology that automates procedures in the cockpit. Although automation has brought considerable benefits to operations and the control of human-machine interaction systems, there is growing empirical evidence pointing to some negative effects, especially regarding human monitoring performance. In light of this, the present research seeks to answer the following question: How can the confusion of thrust modes to which airline pilots are subjected be mitigated when migrating to a new aircraft? This paper aims to propose a training model for pilots transitioning between commercial aircraft, in order to mitigate the adverse effects of automation. To this end, this work proposes the application of a semi-structured questionnaire, used to identify common errors for each type of transition. As partial results, the following most present responses were obtained in situations that may generate confusion, in this order: "interpretation of the modes presented in the FMA (Flight Mode Announcer: the area of the instrument panel that displays the active autopilot and traction management modes) of the aircraft", "sequence of actions during go-around" and "management of vertical navigation". Based on the partial results, a conceptual model was developed in order to add important elements to the training, such as: Pilot Background Assessment, Common Errors Guide and Competence Map of the current Training Program structure - proposed product of this dissertation. The information obtained in this research can be used by airlines to identify situations where mode confusion occurs and apply measures that mitigate the adverse effects of automation.


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