NINA is a research project co-funded by SESAR, as part of its long-term research programme.
It aimed at developing a tool able to perform a real-time assessment on a set of cognitive states of Air Traffic Controllers performing their job – such as mental workload intensity, type of attentional control and proficiency level gained during a training period. The tool uses an algorithm based on the analysis of 3 main neurophysiologic indexes: electrical brain activity, heart rate variability, and eye blinking.
As an integral part of the project, a study to show how the further development of similar kinds of tools could enhance aviation safety and efficiency was performed. This page briefly summarises the results of the study, presenting a proof-of-concept for an advanced system able to understand in real-time the operator’s psycho-physical state, to match it with the situation in which she is operating and to provide the best automated support accordingly.
THE ADAPTATION LOGIC
The system reacts to 3 different sources of disruption (traffic complexity, time pressure and reduced fitness) providing specific support to the 4 main processes controllers have to perform (information acquisition, analysis, action selection and implementation). The level of automation of the solutions ranges from low (the system leaves the human completely in charge) to high (the system decides and implements some actions).
In order to select the best solution to mitigate the performance degradation, the system takes into consideration the three dimensions represented in the cube: source of disruption, stage of information processing to be supported and level of automation to be provided.
ADVANCED ADAPTIVE SOLUTIONS
Have a look at 12 concepts of adaptive solutions.
COMPLEXITY
TIME PRESSURE
FITNESS
ACQUISITION
The adaptive solutions help controllers acquire all the relevant information they need to safely manage the current traffic.
Space Scanner: Low Automation
Priority Spot: Low Automation
Meta Signs: Low Automation
ANALYSIS
The adaptive solutions help controllers correctly understand the meaning of the acquired information.
Dynamic Filter: Medium Automation
Adaptive Label: Medium Automation
Hyperlabel: Medium Automation
DECISION
The adaptive solutions support controllers in selecting the most appropriate action or decision.
Quick Simulation: Low Automation
Multiple Decisions: Medium Automation
Decision Proposal: Medium Automation
IMPLEMENTATION
The adaptive solutions support controllers to correctly execute the selected action.
Communicaiton Highlight: Low Automation
Task Sequencer: High Automation
Auto Control: High Automation
