Innovating Works

HAAWAII

Financiado
Highly Automated Air Traffic Controller Workstations with Artificial Intelligenc...
Highly Automated Air Traffic Controller Workstations with Artificial Intelligence Integration Advanced automation support developed in Wave 1 of SESAR IR includes using of automatic speech recognition (ASR) to reduce the amount of manual data inputs by air-traffic controllers. Evaluation of controllers’ feedback has been s... Advanced automation support developed in Wave 1 of SESAR IR includes using of automatic speech recognition (ASR) to reduce the amount of manual data inputs by air-traffic controllers. Evaluation of controllers’ feedback has been subdued due to the limited recognition performance of the commercial of the shell ASR engines that were used, even in laboratory conditions. The reasons for the unsatisfactory conclusions include e.g. inability to distinguish controllers’ accents, deviations from standard phraseology and limited real-time recognition performance. Past exploratory research funded project MALORCA, however, has shown (on restricted use-cases) that satisfactory performance can be reached with novel data-driven machine learning approaches. Based on the results of MALORCA HAAWAII project aims to research and develop a reliable, error resilient and adaptable solution to automatically transcribe voice commands issued by both air-traffic controllers and pilots. The project will build on very large collection of data, organized with a minimum expert effort to develop a new set of models for complex environments of Icelandic en-route and London TMA. HAAWAII aims to perform proof-of-concept trials in challenging environments, i.e. to be directly connected with real-life data from ops room. As pilot read-back error detection is the main application, HAAWAII aims to significantly enhance the validity of the speech recognition models. The proposed work goes far beyond the work planned for the Wave 2 IR programme and will improve both safety and reduce controllers’ workload. The digitization of controller and pilot voice utterances can be used for a wide variety of safety and performance related benefits including, but not limiting to pre-fill entries into electronic flight strips and CPDLC messages. Another application demonstrated during proof-of-concept will be to objectively estimate controllers’ workload utilising digitized voice recordings of the complex London TMA. ver más
30/11/2022
DLR
2M€
Duración del proyecto: 28 meses Fecha Inicio: 2020-07-23
Fecha Fin: 2022-11-30

Línea de financiación: concedida

El organismo H2020 notifico la concesión del proyecto el día 2022-11-30
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
SESAR-ER4-18-2019: Automation and CWP
Cerrada hace 5 años
Presupuesto El presupuesto total del proyecto asciende a 2M€
Líder del proyecto
DEUTSCHES ZENTRUM FUR LUFT UND RAUMFAHRT EV No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5