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HUMAN

Financiado

Cerrado

Model Based Analysis of Human Errors during Aircraft Cockpit System Design

The objective of the HUMAN project is to develop a methodology with techniques and prototypical tools supporting the prediction of human errors in ways that are usable and practical for human-centred design of systems operating in... ver más

31/08/2011

OFFIS EV

4M€

Presupuesto del proyecto: 4M€

Líder del proyecto

OFFIS EV No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 6 Participantes

Financiación concedida El organismo FP7 notifico la concesión del proyecto el día 2011-08-31 No tenemos la información de la convocatoria

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6 Participantes

OFFIS EV

0.00€ | Lider

NETHERLANDS ORGANISATION FOR...

N.D. | Participante

AIRBUS OPERATIONS

N.D. | Participante

UCLouvain

N.D. | Participante

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Líder del proyecto

OFFIS EV No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 4M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The objective of the HUMAN project is to develop a methodology with techniques and prototypical tools supporting the prediction of human errors in ways that are usable and practical for human-centred design of systems operating in complex cockpit environments. The methodology contributes to (1) reducing the accident rate by enhancing the accuracy of pilot error prediction and to (2) achieving a substantial improvement in the elimination of and recovery from human error by reducing the effort of design and test for active and passive safety measures. These targets will be achieved through research and technology development in: (1) Cognitive modelling: the challenge is to develop an integrated cognitive crew model able to predict a significant range of design relevant pilot behaviours (including errors) covering human-machine interaction and crew performance in the complex dynamic environments. (2) Virtual simulation: the challenge is to develop a high-fidelity virtual simulation platform to execute the cognitive crew model in realistic flight scenarios in order to analyse the dependencies (including the safety effect of likely pilot errors) between the pilots, a target system, the aircraft and its environment. (3) Knowledge base on human performance: the challenge is to thoroughly investigate pilot behaviour on a physical simulation platform (comprising a full-scale flight simulator) to enhance the understanding of cognitive processes leading to pilot errors and to use the resulting knowledge to validate and further develop the cognitive crew model. The human errors will be studied in relation to a target system that will be based on issues pertaining to the future Air Traffic Management context. This will permit to study pilots' future activities and potential errors and to provide useful information to drive the development of active and passive safety measures for this domain.

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