MOTO: the embodied reMOte TOwer

What is Moto Project?

Funder & Duration

  • Funder: Horizon 2020, Call: H2020-SESAR-2015-1, Topic: Sesar-06-2015 High Performing Airport Operations, Grant Number: 699379.
  • Duration: 2 years

In Europe, there are many small airports and the importance of these regional airports continuously increases with the advent of low-cost carriers. For these airports, it is more and more difficult and costly to have air traffic controllers staffing and controlling. In order to improve safety and traffic regulation, many European countries are in process of developing remote tower management. The idea is that the person monitoring and controlling the traffic does not have to be located in the tower itself, but can operate from a distant site. This new system is supposed to allow monitoring the traffic in small airports thanks to cameras, radar screens and radio transmission. The operator would control the airport by looking at screens where the situation is displayed in a similar way as what s/he could see "out of the window" in a tower on the airport.

Objective:
In this project, the purpose is to develop technologies to enhance the current Remote Tower concept, by integrating multimodal human-system interaction.

Partecipants:

  • ENAC (École nationale de l'aviation civile): Training school for Air Traffic Controllers and Airplain Pilots
  • Unversità "Sapienza": Experts in augmented reality and neurometrics assessment
  • Università di Groningen: Expert in machine learning techniques
  • Deep Blue: Experts in Human Factor concepts, safety and validation.

 

Publications related to this line of research

  • Aricò, P., Borghini G., Di Flumeri G., Colosimo A., Bonelli S., Golfetti A., Pozzi S., Imbert J.P., Granger G., Benhacene R., Babiloni F. “Adaptive Automation triggered by EEG-based mental workload index: a passive Brain-Computer Interface application in realistic Air Traffic Control environment”. Submitted on Frontiers in Human Neuroscience journal, 07/2016.
  • Borghini G., Aricò P., Di Flumeri G., Cartocci G., Colosimo A., Bonelli S., Golfetti A., Pozzi S., Imbert J.P., Granger G., Benhacene R., Babiloni F. “EEG-Based Cognitive Control Behaviour Assessment: an Eco-logical study with Professional Air Traffic Controllers”. Submitted on Scientific Reports journal, 07/2016.
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