Neurometrics INdicators for ATM (NINA)

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Despite the benefits and huge advances in (aviation) automation over the last decades, the current automated tools are in many cases unaware of the ‘bigger picture’. That is, they are not yet able to understand the intentions of users or the intricacies of the environment it is operating in. When the level of automation support in future air traffic control increases, the automated systems will need more awareness about the dynamic context in which they operate.
The broad aim of this research is to provide fundamental insight into, and practical experience with, the difficult challenge of adaptive automation and level of automation transitioning in a human-centred air traffic control work environment. An innovative element in this research project is the development of autonomous, environmentally-driven adaptive automation, where the appropriate level of automation will be determined by the functional demands of the operational context. The goals are: (1) to discover the metrics that constitute an operational context, and (2) to develop a rule base for level switching and human-machine interface adaptation.

UTOPIA (Universal Trajectory Synchronization for Highly Predictable Arrivals Enabled by Full Automation) was funded by EUROCONTROL as part of the SESAR Workpackage E (WP-E) from 2011 until 2013. It was a joint effort of Boeing Research & Technology Europe, Barco-Orthogon and TU Dresden acting as project coordinator.


Date of filing: 23 May 2014

Application No./Patent No. 14382181.7-1803



Date of filing: 30 Jan 2014

Application No./...

SCALES: Resilience potential and early warnings for Air Traffic Management in case of system degradation through Enterprise Architecture.

SINTEF Information and Communication Technology (NOR)

Deep Blue (IT)



Application of the Theory of Formal Languages to the Modeling of Trajectory Uncertainty and the Analysis of its Impact in Future Trajectory-Based Operations. E. Casado, C. Goodchild, M. Vilaplana. 1st International Conference on Application and Theory of Automation in Command and Control Systems (ATACCS’2011). Barcelona.


Overcoming the traditional human-automation issues is a challenge that has been addressed by many research works. Design choices like picking the right level of automation (or deciding for an adaptive automation), or correctly distributing roles and tasks between the human and the system etc. are very important decisions that deserve robust foundations in order to “build the system right”. However, what do we do after we have made those choices? How is the automation affecting the real interaction with the operator and how do we cope with that?

1. Objective

The introduction of automation is considered to be a key step in bridging the expected gap between capacity and demand in the harmonization of the European Airspace (SESAR). The allocation of automated functions to a system is often assumed to be associated with an increase in efficiency and safety performance. The rationale behind this reasoning is that the technical systems will be able to perform more reliable than a human operator regarding specific functions.

AUTOFLY-Aid will study “dynamic 4D trajectory management” to be implemented above the basic/passive TCAS solution using the on-board avionics and the SESAR enhanced flight deck situational awareness, coming from CNS (primarily ADS-B and its enhancements) and SWIM network. The “dynamic 4D trajectory management” is to be based on a hybrid and stochastic airspace model not only representing uncertainties associated with sensed and received airspace traffic and intent information, but also representing limitations associated with weather, terrain/obstacle and new conflict hazards. As an end result, the overall automation support system which embeds “dynamic 4D trajectory management” is envisioned to a) provide the pilots with alternative trajectories as tunnels-in-the-sky through avionics displays on the console and head-up displays in real-time, b) provide the flight crew with quantified and visual understanding of collision risks in terms of time and directions and countermeasures, and c) provide autonomous conflict resolution as an autopilot mode. Thus, ensuring highly responsive and adaptive airborne collision avoidance in face of ever challenging scenarios that involve blunders, weather/ terrain/ obstacle/ new conflict hazards. These algorithms and tools developed are currently being integrated on an Automation Support System for implementation on a Boeing 737 Flight Simulator with synthetic vision and reality augmentation.