STRESS is a SESAR 2020 project addressing human performance in future air traffic management (ATM) scenarios. The project started in June 2016 and finished in June 2018.
STRESS studied the impact of advanced highly automated systems on air traffic controllers’ performance.
The project developed a mental state measurement toolbox (also called the “neurometrics toolbox”) capable of providing, with high-time resolution, neurophysiological indicators of workload, vigilance, attention, stress and cognitive control behaviour. This toolbox facilitated the understanding, modelling and analysis of changes in the human performance envelope when reacting to different automation types and levels.
STRESS will support the SESAR transition to higher levels of automation in ATM, providing guidelines for the design and implementation of future technologies for air traffic control. The aim is to obtain balanced human-machine cooperation and to ensure safe transitions from high to low automation levels (e.g. automation failures), and vice versa.