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AUTOMATION PACE

Periodic Reporting for period 4 - AUTOPACE (AUTOMATION PACE)

Période du rapport: 2017-09-01 au 2018-02-28

AUTOPACE is a project funded by the SESAR Joint Undertaking within the European Union’s Horizon 2020 research and innovation programme under grant agreement No 699238. AUTOPACE responds to the first Call for Proposals of SESAR Exploratory Research projects. Particularly AUTOPACE addresses the Research Topic ER-01-2015: Automation in ATM starting in TRL 0 (Technology Readiness Level) and aiming at finalising in TRL 1. AUTOPACE is focused in En-Route environment and 2050 timeframe.

The Air Traffic Management (ATM) system moves towards an increasingly high level of automation that will unavoidably change the ATCo work environment and the role of the human. Air Traffic Controller will perform tasks focused on monitoring and supervision of the system actions keeping the tactical interventions to a minimum. However, human-automation interaction in highly automated environments presents serious performance drawbacks due to the risk of the “out of the loop” effect (OOTL) especially in case of automation fail or fears of automation when a fail might occur. Future ATCos should be trained not only to acquire new technical competences but also to acquire psychological cognitive and non-cognitive competences for keeping attention to avoid the OOTL effect and for coping with stress or fear of system failure. AUTOPACE aims at supporting a better understanding on how cognition and automation live together to support new training strategies and automation suitability assessment.

To address these needs, AUTOPACE Consortium assembles five organisations with a large experience on the field of ATM psychological modelling and ATM system operations. AUTOPACE is led by CRIDA, the R&D+i Centre of the Spanish Air Navigation Service Provider (ENAIRE) and formed by the University of Granada – Faculty of Psychology, the Polytechnic University of Madrid – School of Controllers; the University of Bologna; and the University of Belgrade - Faculty of Transport and Traffic Engineering.
"AUTOPACE has defined a Concept of Operation and future Automation Scenarios in nominal and non-nominal situations identifying new roles and responsibilities for ATCo with the system-human function allocation foreseen at 2050 time horizon. Due to the level of uncertainty on how automatic systems will be in 2050, two different levels of automation are described (Medium and High Automation) with different roles and responsibilities for ATCo.

A research on an ATCo Psychological Model based on established attentional theories to predict the effects of automation on the ATCo performance has been done. Particularly: (a) an estimation on how the ATCo cognitive system structure changes with automation as the future ATCo shall focus his/her cognitive effort on mainly comprehension and projection processes for situational awareness acquisition (monitoring and supervision); (b) the identification of the ATCo performance drawbacks due to the risk of the “out of the loop (OOTL)” and “fear of automation” whose consequences are especially severe in case of automation failure; and (c) hypotheses collecting how the ATCo performance in terms of Mental Workload will be affected by automation along with a preliminary experimental plan to validate them in future research.

Besides, the identification of new ATCo Competences and a Training Strategies catalogue is defined addressing not only the technical system interaction needs but also the psychological (cognitive and non-cognitive) aspects to mitigate the ATCo performance drawbacks due to automation. This research has also provided a feasibility study on a validation platform to emulate future ATCo and system responsibilities to be used for further validation and some conclusions on selection criteria along with prerequisites on Skills, Abilities and Personality Characteristics for future ATCos.

A Preliminary Safety Hazard Assessment (PHA) in future automation Scenarios for nominal and non-nominal situations has been done to provide a set of automation risks that should be mitigated by modifying ATCo training or refining the system and procedure design. Based on this analysis, training strategies have been refined to mitigate those related hazards. Recommendations on system features and operational procedures for high automation environments to address those risks not covered or mitigated with ATCo future competences and training are also defined.

Finally a Qualitative Performance Assessment (CAP, CEFF, HP) has shown the benefits brought by AUTOPACE concept elements.

AUTOPACE Project was presented at UPM Summer Course 2016 ""ADDRESSING AVIATION AND ATM SAFETY CHALLENGES” (July 2016); in SESAR Innovation Days at Delft (November 2016), in the South East Aviation Summit - SEAS (December 2016),the World ATM Congress (March 2017), FRAMily workshop (May 2017), SAFE 2017 (September 2017), SYMOPIS 2017 (September 2017), 7th EASN International Conference (September 2017), 7th SESAR Innovation Days (November 2017) and TRB 2018 (January 2018). Two workshops (March, 2017 at Madrid and November, 2017 at Belgrade) and one Final Dissemination Event (March 2018 at Madrid) have been organised.
A poster, papers and articles (11 in total) have been prepared and submitted during the project life.



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The identification of the required new competences and training to operate in a future highly automated environment will allow the European Community to effectively implement advanced automation features, ensuring adequate safety level (Safety) and optimized implementation costs in terms of training and technology adaptation (Cost-Efficiency and Human Performance). Moreover, the delivery of an effective ATCo Training Curricula and Personnel Selection Process will accelerate the training path and increase the productivity of the ATCo operating in the foreseen environment (Cost-Efficiency and Human Performance).

The availability of an ATCo Psychological Model will allow establishing the ATCo Mental Workload level that can optimise the level of activation and engagement thus maximising the ATCo productivity within a desired safety level (Capacity, Cost-Efficiency and Safety). This Psychological Model will predict ATCo Mental Workload based on the cognitive resources that the ATCo will require when working in a highly automated environment and it will allow risk assessment based on the provided cognitive values.

The assessment of the automation features to support future ATCo will contribute to the increment of the ATCo productivity (Cost-Efficiency). This identification will also offer to the industry some advice about the areas to be researched when developing new technology to support the future ATM system. For this reason, the availability of methodologies to estimate the performance benefits of automation will increase the effectiveness of their design thus optimising the use of the airspace (Capacity). In turn, a preliminary Hazard Assessment of AUTOPACE Future Automation Scenarios will support the identification of a set of automation risks that should be addressed by introducing training or refining the automation design, ensuring that safety can be properly addressed for the automation features expected in future ATM (Safety).