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AUTOMATION PACE

Periodic Reporting for period 3 - AUTOPACE (AUTOMATION PACE)

Reporting period: 2017-03-01 to 2017-08-31

AUTOPACE is a research project funded by the SESAR Joint Undertaking within the European Union’s Horizon 2020 research and innovation programme under grant agreement No 699238. It performs fundamental research on psychological modelling to predict how future automation would impact on air traffic controller (ATCo) performance and to identify competences and training to cope with the effects of automation on humans.

Automation will unavoidably change the ATCo work environment and the role of the human will move towards 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.

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 – Aerospace Systems, Air Transport and Airports Department; the University of Bologna; and the University of Belgrade - Faculty of Transport and Traffic Engineering.

AUTOPACE aims at supporting a better understanding on how cognition and automation live together to support new training strategies and interface design. To do so, AUTOPACE research path is oriented to develop an ATCo psychological model to quantitatively predict how automation impact on performance based on a representation of human cognitive system and established psychological attentional theories. This model would allow prediction of optimal states of human-automation interaction to ensure a safe operation.
"AUTOPACE has defined a future concept of operations expected for 2050 where the traffic characteristics and operational procedures, the ATC systems functionalities, and the ATM actors are described based on the 2050 foreseen developments in Air Traffic Management (ATM). Due to the high uncertainty on how the system-controller function allocation will be at 2050 horizon, AUTOPACE has defined two future automation scenarios in nominal and non-nominal situations representing:
- A high degree of automation where the ATC System develops the necessary actions for the orderly and safely traffic management, informing the ATCo. Hence the ATCo responsibilities are oriented to monitoring and approving.
- A medium degree of automation where the ATC System proposes actions and the ATCo decides which action to apply from the set of proposals displayed. ATCo responsibilities are monitoring, approving and sometimes applying.
Based on these scenarios and established attentional theories, AUTOPACE has researched about an ATCo Psychological Model to predict the effect of automation in ATCo performance. AUTOPACE psychological model considers the description of two main components: the functional structure of the cognitive system and its attentional resources for its functioning to carry out ATCo task. This model has been used to estimate how the different mental resources would vary on AUTOPACE scenarios through the modelling of the ATCo task. A preliminary Experimental plan has already defined for further research projects.
A Safety Hazard Assessment has been completed identifying situations where safety of future automation scenarios might be negatively affected. For that purpose, identification and qualitative analysis of Safety hazards for safety critical situations through brainstorming sessions with operational experts (ATCo’s) have been made and assessed. A set of automation risks have been analysed introducing training or refining the automation design as mitigation actions.
In progress and based on the Psychological Model research and automation risks identification, a competency-based training and assessment methodology is being followed to identify the competences and new training strategies for future ATCos. The new training strategies are addressing not only the technical aspects to operate with highly automated systems but also with the effects of automation (out-of-the-loop/overconfidence or disorientation, overacting or erratic behaviour/ fears of failure). AUTOPACE dissemination activities follows AUTOPACE Dissemination and Exploitation Plan. 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) and FRAMily workshop (May 2017). Two workshops have been organised in the framework of AUTOPACE and several collaboration initiatives with other research projects have been carried out.
Some papers have been prepared and submitted during this reporting period.
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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).