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Human Performance neurometricS Toolbox foR highly automatEd Systems deSign

Periodic Reporting for period 4 - STRESS (Human Performance neurometricS Toolbox foR highly automatEd Systems deSign)

Reporting period: 2017-12-15 to 2018-06-14

The European ATM system is expected to face challenging situations, with the growth of air traffic, the increase of its complexity, the introduction of innovative concepts and increased automation. The roles and tasks of air traffic controllers (ATCOs) will change in the future and it is vital to enhance the comprehension of human responses to their role changing, that is, from active control to monitoring of complex situations and managing unexpected system disruptions.
The main goal of the project is to generate knowledge able to support the design of the technologies which will be used by controllers to manage the future air traffic scenario. Specifically the project will provide guidelines to be followed to project future systems that are compatible with human capabilities and limitations, ensuring that the right balance between humans and automations is obtained.

The project is divided into four phases:
• Future scenarios: understand how ATM will develop in the coming years and how controllers’ role will change
• Human Performance Indexes: develop and validate a set of tools able to objective measure controllers’ stress, workload and attention through the analysis of brain waves, heart rate, eyes movement and skin conductivity
• Experiments: simulate future highly automated systems and use the indexes to assess their impact on human performance
• Design guidelines: based on experiments results, develop guidance for the development of systems correctly balancing automation and humans’ roles, able to support the transition among different automation levels and supporting humans in handling automation errors and failures.

Each one of them contributes to the project with unique expertise: a strong understanding of Human Factors (Deep Blue), a solid experience in the use of neurophysiologic measurements (Sapienza University), a deep knowledge of air traffic management domain (ENAC and Anadolu University) and a overall view on what is the strategic agenda for the development of this domain in the upcoming years (EUROCONTROL).

The project lasted 2 years, from June 2016 to June 2018. More information available at http://www.stressproject.eu/. Project contacts: Stefano Bonelli stefano.bonelli@dblue.it and Martina Ragosta martina.ragosta@dblue.it
The project research plan addressed the Human Performance issues, benefits and impacts of the SESAR paradigm shift towards increasing automation levels.

Most of the proposed changes deriving from the implementation of the SESAR solutions are expected to increase the pilot’s autonomy in controlling the route of their aircraft, including the requirement to maintain required separation between aircrafts. Flight time, delays and fuel expenditures are all expected to profit from such changes. At ground level, this corresponds to a change in the role of Air Traffic Controllers (ATCOs), shifting from active controller to monitoring one. To support Air Traffic Control operations, SESAR is working to introduce higher levels of automation, to the extent that the new generation of automated systems for Air Traffic Control (ATC) are expected to autonomously (or partially autonomously) manage decision-making and action-implementation tasks, generally carried out, at the current moment, by ATCOs. The latter are still responsible for running the ATC system safely, but their role would move from active control to monitoring of complex situations and managing unexpected system disruptions. It is vital to enhance the comprehension of the ATCOs responses to such role changing. STRESS dealt with it.

In its two years, STRESS developed the following technical contributions to tackle the aforementioned problems:

• Future ATC scenarios including highly automated supporting technologies, for assessing the changes in human roles in higher automation scenarios.
• Validated mental states measurement toolbox and neurophysiological signals fusion-based methodology to monitor with high time resolution the levels of vigilance, attention, stress, workload and cognitive control behaviour of Air Traffic Controllers in realistic operational environments.
• Guidelines for the design, implementation and training of innovative technologies that are compatible with human capabilities and limitations.
• A White Paper on follow-up research activities, in cooperation with other SESAR Exploratory Research projects.

The participation in various events has helped disseminate the STRESS approach. Aviation stakeholders provided positive feedback on the project results, and also gave advice for the application of the STRESS approach. In particular, they highlighted that the mental state measurement toolbox developed by STRESS could be applied at several ATM organizational levels, as follows:
• As a training tool, to assess the level of expertise and feed debriefings
• As an automation evaluation tool, useful to assess new systems from a HP perspective and also to compare the HP impact of different solutions
• For research in the area of safety and HP, for example ageing performance
• In operations, to support workers in difficult situations (stress, overload, fatigue, etc)
The main topics that will be improved thanks to STRESS:
1. Considered Human Factors description in terms of specific cognitive processes and mental states.
2. Neurophysiological characterization of stress, attention, cognitive control and workload phenomena.
3. Combination of the indexes to test the possibility to simultaneously measure such mental states along the execution of tasks.
4. Testing of Automation and its impact\relation to Human Performance

In particular, the mental state of stress, attention, cognitive control and workload have been characterised by means of specific cognitive processes.
Neurometrics have then been defined by combining the considered neurophysiological signals with the aim to measure and track such mental state changes along the execution of laboratory tasks.
The signals have been chosen in a way that different human factors can be measured at the same time.