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AUTOPACE DISSEMINATION WORKSHOP, NOVEMBER 27, 2017, BELGRADE

AUTOPACEDISSEMINATION WORKSHOP REPORT

27/11/2017

Meeting: AUTOPACE Dissemination Workshop

Date / Time: 27/11/201 14:00 -18:00

Location: UB-FTTE, Belgrade, Serbia

Chairman: Patricia López (Project Coordinator)

Participants:

# Name E-mail Role/Expertise Organisation

1 Kevin Le Goff [email protected] Human Factors Airbus

2 Alexander Zarbov

[email protected] ATCo/Expert PS BULATSA

3 Zoran Jakšić [email protected] Automation in ATCATCo, Instructor

Croatia Control Ltd.

4 Åsa Svensson [email protected] Science and Technology

Linköping University

5 Jonas Lundberg [email protected] Science and Technology

6 Carl Westin [email protected] Science and Technology/AF

7 Anne Baumgarten

[email protected] Project Execution Manager & SESAR Deployment Coordinator

DFS

8 Isabel Metz [email protected] ATM Simulations DLR

9 Pierre Andribet [email protected] Head of R&D and SESAR contribution

ECTRL10

Sebastian Wangnick

[email protected]

HMI

1 Julie SAINT-LOT [email protected] ATM ENAC

© – 2016 – AUTOPACE Consortium. All rights reserved. Licensed to the SESAR Joint Undertaking under conditions.”

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1

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Ioannis Trakas [email protected] Air Traffic Safety Electronics Associations

IFATSEA13

Kostas Simonakis Air Traffic Safety Electronics Associations

14

Magnus Nylin [email protected] System Engineer (M.Sc. in Cognitive Science, B.Sc. in Informatics)

LFV15

Billy Josefsson [email protected] ATCo/Manager Automation & Human Performance

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Babić Danica [email protected] Assistant Professor,Airline Operations

UB-FTTE17

Jovana Kuljanìn [email protected] PhD student

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Bruno Barberian [email protected] ONERA

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Luca Crecco [email protected] SJU Programme Management

SJU20

Alessandro Prister

[email protected] SJU Programme Management

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Milan Jovanović [email protected] ATCo SMATSA

22

André Jover [email protected] IT

SOPRASTERIA23

Sébastien Arqué [email protected]

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Milan Janic [email protected] Professor, Transportation Planning, Modeling TU Delft

25

Junzi Sun ATM-CNS

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Ivana Francetić [email protected]

University of Zagreb-Department of Aeronautics

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Biljana Juričić [email protected],[email protected]

Assistant Professor, ATC/ATM

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Doris Novak [email protected],[email protected]

Associate Professor, ATC/ATM

2 Tomislav Radišić [email protected] Assistant Professor,


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9 ATC/ATM

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Bruno-Antulov Fantulin

[email protected] Teaching and Researcg Assistant, ATC/ATM

31

Petar Andraši [email protected] Teaching and Researcg Assistant, ATC/ATM

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Jurica Ivošević [email protected] PostDoc

AUTOPACE Partners

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Patricia López (PL)Elena López (EL)

CRIDA (Spain)

3 Fernando Gómez (FG) Polytechnic University of Madrid/UPM (Spain)

4567

Fedja Netjasov (FN)Bojana Mirkovic (BM)Obrad Babic (OB)Tatjana KrsticSimic (TK)

University of Belgrade/FTTE (Serbia)

89

Francesca De Crescenzio (FC)Francesca Lucchi (FL)

University of Bologna/UNIBO (Italy)

1011

Pedro Ferreira (PF)Jose J. Cañas (JC)

University of Granada/UGR (Spain)

Workshop Objectives and Agenda

AUTOPACE Dissemination Workshop is twofold:

To present of AUTOPACE main achievements To get feedback on future research areas on automation

In order to ensure the accomplishment of these objectives, the workshop was organised in two main sessions: a first session where project was presented by AUTOPACE partners along with the main achievements and possible research areas, and a second part where a game was organised to get a prioritization of further research areas from the audience based on a set of proposed topics obtained during AUTOPACE Research.

Duration Item Topic Who

14:00-14:20 #1 Welcome, Agenda and Workshop Objectives PL (CRIDA)

14:20-14:30 #2 AUTOPACE Project Presentation PL (CRIDA)

14:30-15:30 #3 Presentation of AUTOPACE FL (UNIBO), JC (UGR), FG


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Duration Item Topic WhoAchievements and Potential Further

Research Areas (UPM), BM (UB-FTTE)

15:45-16:40 #4 GAME: Prioritization of Research Areas ALL-working in groups

16:40-17:40 #5 GAME: Prioritization of Research Areas (Cont.) ALL

17:40-18:00 #6 Wrap-Up: Results of Prioritization PL (CRIDA)

AUTOPACE Project: Main Achievements and Research Areas

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. Particularly AUTOPACE addresses the Research Topic ER-01-2015: Automation in ATM with the aim of increasing the awareness of the interaction between automation and human performance. AUTOPACE is a fundamental research project aiming at achieving TRL 11.

The project started on March 1st, 2016 and has two years duration.

Automation will unavoidably change the Air Traffic Controller (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 ATCo 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 participated by the University of Granada – Faculty of Psychology, the Polytechnic University of Madrid – Aerospace Systems, Air Transport and Airports

1 Technology Readiness Levels (TRL) are a type of measurement system used to assess the maturity level of a particular technology. Each technology project is evaluated against the parameters for each technology level and is then assigned a TRL rating based on the projects progress. There are nine technology readiness levels. TRL 1 is the lowest and TRL 9 is the highest. When a technology is at TRL 1, scientific research is beginning and those results are being translated into future research and development.


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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. In turn, this model allows supports the research of the future required competences and training strategies to ensure a safe performance at high automated environments.

Future Automation Scenarios for 2050 (for details see ppts attached)

The first step of the project was the development of the 2050 ConOps and scenarios. The AUTOPACE ConOps definition has been performed on the basis of a literature research. Several documents were considered as relevant to achieve a common understanding on the state of the art on future automation developments in Air Traffic Control. A reference list was identified considering two different time horizons (2035 and 2050):

2035 AUTOPACE ConOps has been defined based on SESAR Step 2 deliveries, as a good picture of what will be in place by this time. It constitutes a robust, well-structured baseline upon which 2050 environment can be developed.

2050 AUTOPACE ConOps has been developed upon 2035 AUTOPACE ConOps using as primary references Flight Path 2050 document; ACARE SRIA – Strategic Research and Innovation Agenda, EREA From Air Transport System 2050 Vision and HALA! Position Paper 2014.

2050 AUTOPACE ConOps were derived to Operational Scenarios: they consist in a description of how a future system could work, considering user’s behaviour, the interaction between user and future


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system, and the wider context of use. For each scenario, several use cases describe the set of circumstances, where the user interacts with the system as identified by a group of expert in the matter of study.

Since, there is still much uncertainty about what degree of automation will be deployed, AUTOPACE has considered two different degrees of automation for ConOps definition and for the scenarios, that affect ATC controller role:

High Automation Scenario: This scenario has a high degree of automation. The ATC System develops the necessary actions for the orderly and safely traffic management, informing the ATC controller of the actions developed if requested. The ATC controller maintains a monitoring function.

Medium Automation Scenario: This scenario has a medium degree of automation. The ATC tools will propose actions to be performed, and the ATC controller will decide which action to apply from the set of proposals suggested by the system. Tasks are shared between ATC system and controller.

AUTOPACE Non-nominal situations consider an automation failure or a malfunction in the service provision of one or several ATC tools. In this perspective, three system’s failures have been identified for AUTOPACE purposes: (1) The Conflict Detection and Resolution tool fails; (2) The Complexity management tools fails; (3) The System supported coordination tools fails.

Further Research on Future Automation Scenarios

RA#1: Future ATC System Development: In the Future Automation Scenarios context, the Research Area focuses on a description refinement of future concept of operation and scenarios for 2050 time horizon. The level of uncertainty at this timeframe supposes many assumptions for roles and responsibilities for controller and system along with system requirements and the identification of non-nominal situations.

RA#2: Investigate on regulation and standardization issues related to new responsibilities allocation in high automation scenarios: The new function allocation between system and human implies substantial changes in current regulation and standardization frameworks. This research area proposes to investigate how to tackle with these changes to ensure the feasibility of the new roles and responsibilities for ATCos.

RA#3: Validation of the “Apply – Approve – Monitor” responsibilities for ATCo activity as for the definition of AUTOPACE Future Automation Scenarios the responsibilities that are expected to be allocated to ATC actors (System and the ATCo) have been described by using three actions: Apply, Approve, and Monitor: (a) Monitor when the ATC system is assuming the major tactical actions and the ATCo has to monitor its behaviour to prevent system deviations, (b) Approve, once the ATC system has proposed a solution for an ATC intervention, the ATCo must approve it in order to be implemented (c) Apply, the ATCo analyses the situation, decides and implements the most suitable solution from those proposed by the ATC system according to the information provided by the ATC tools. Furhter research is needed to validate the refinement of these responsibilities between system and ATCo.


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RA#4: Definition of different non-nominal scenarios: The selection of potential failures to be considered as non-nominal situations has taken two assumptions: (1) the ATC responsibilities should still be carried out even though some services provided by tools are disabled and (2) the ATCo will need to change their mode of operation in order to assume the ATC responsibilities that the ATC system will not take during the failure or to operate with the absence of some system functions such as lack of information, support services, etc. New assumptions might be needed to refine the existing non-nominal scenarios considering different severity of failures. Also new different system failures or other circumstances could be analysed for non-nominal situations.

ATCo Psychological Model (for details see ppt attached)

The ATCo psychological model is thought as a representation of human cognitive system and established psychological attentional theories to predict the effects of automation on the ATCo performance. For the purpose of developing an ATCo psychological model, two sub-models are considered: (a) the Cognitive Process Model that is the functional structure of the cognitive system and (b) the Mental Workload Model that represent the mental resources needed to ensure the cognitive processes functioning.

The cognitive system has structural components whose functions are the processing of information from outside, the storing of the results of that processing, and the responding to the environment. AUTOPACE takes as reference the model proposed by Histon and Hansman. The ATCo cognitive processes that underpin his/her functional structure of the cognitive system are: Perception, Comprehension, Projection (Situation Awareness/SA Processes), Decision Making (Decide Process) and Execution (Execution Processes). Due to the ATCo activity, the two main channels for perception are visual and auditory, and the two main channels for execution are manual and verbal.

For explaining the functioning of the ATCo Cognitive System, AUTOPACE uses two concepts, demanded and available resources. While demanded resources are those required by the task and essentially dependent on the task complexity, available resources are the resources that the ATCo has that could be used to perform the task. The fundamental premise of all the models is that the functional structures, such as those described above, will work with an efficacy that will depend on the relationship between the demanded and the available resources. This relation is called the Mental Workload (MWL).

According to established attentional theories, the impact of automation on the cognitive functioning and mental resources will be different. Following the classical theory (Kahneman, 1973) automatic systems only reduce the task complexity and hence the demanded resources. But new theories such as the Malleable Attentional Resources Theory (MART) (Young and Stanton, 2002) assume that automation impacts not only the demanded resources but also the available resources depending on the human expectations. When the operator expects that the task will be easy, she/he will reduce available resources (low level of activation) and there would be more risk of OOTL effect. On the contrary, if the ATCo feels fears of automation failing, the stress would increase the level of activation and then the amount of available resources.

In turn different level of automation would mean different responsibilities. Each of these responsibilities would require different levels of engagement with the task and Situational Awareness (Metzger and Parasuraman, 2001) meaning that with high automation levels where ATCo tasks are mainly monitoring, would imply less engagement with the task and therefore less available resources dedicated to the task (more risk of OOTL effect). On the contrary, when the ATCo has the


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responsibility for applying actions, he/she has more engagement with the task (more activation levels) and more probability of being affected by fear of failure.

By using an existing computational prototype developed by CRIDA called COMETA (COgnitive ModEl for aTco workload Assessment) and a Fast Time Simulator (RAMS- Reorganized ATC Mathematical Simulator) to model future 2050 scenarios, the cognitive demand has been estimated finding that the distribution of the functional structure of the cognitive system changes drastically with automation. While current ATCo uses the cognitive dimensions (visual, comprehension, projection, decision making and verbal resources) in a balanced way, the future ATCo shall focus his/her cognitive effort in mainly comprehension and projection. The ATCo needs to project what is going to happen to understand the system performance without missing Situational Awareness.

Further Research on ATCo Psychological Model

RA#5: Validate the combination effect of automation on the level of activation (overconfidence, fears of automation) in simulated environments: The level of activation increments the pool of available resources and decreases with the operator trust on the system. The more is the trust, the less is the level of activation (the less is the pool of available resources). As High Automation implies complex systems and opacity, the ATCo tends to not trust the system and as a consequence the level of activation is higher. But independently of the level of automation (high or medium), if the ATCo fully trusts the system, the reduction of the level of activation creates an OOTL effect being in an unsafe situation in case of system failure. When the ATCo does not trust the system, the level of activation can be so high that panic, disorientation or erratic behaviour can be observed. In turn the ATCo engagement with the task affects the pool of available resources as the level of activation does. The combination of situational trust, learned trust and engagement need to be further analysed as it is unclear the combined effect of both trust aspects.

RA#6: Investigation on computerization of ATCo Psychological Model to quantify the automation effects on ATCo Performance: The modelling of demanded resources is a reality (COMETA prototype is already developed) but in case of the available resources, first it is necessary to validate the total effect of automation on available resources (previous research area). At this point a development of a computerised model to be used for prediction of automation on ATCo performance will be closer to reality. This would give the potential to quantify ATCo performance for any level of automation and new concepts of operation.

RA#7: Research on ATCo supporting tools design to boost the use of required cognitive processes (comprehension and projection) affected by future automation. The estimation of cognitive demand (demanded resources) in high and medium automation scenarios for 2050 has shown that the use of comprehension and projection cognitive processes are more demanded than Perception, Decision Making and Execution. A good acquisition of Situational Awareness is key to monitor/understand what the system is doing and therefore to detect if the system is making errors. Supporting tools for the ATCo to improve the acquisition of a good SA are proposed for research.

Training Strategies (for details see ppt attached)

As a consequence of the introduction of automation in ATC, performance drawbacks might occur such as the mentioned out of the loop effect (OOTL) or the appearance of panic and erratic behaviours as consequence of an automated system failure. Future ATCos should be trained not only to acquire new technical competences to interact with the system but also to acquire psychological


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cognitive and non-cognitive competences for keeping attention to avoid the OOTL effect and for coping with stress or fear. Psychological Cognitive Training is oriented to strengthen the use of appropriate cognitive processes, particularly Comprehension and Projection. Psychological Non-Cognitive Competences is oriented to avoid OOTL/Panic and keep engagement with the task.

Technical Training Strategy is divided in three phases:

Basic Training: Theoretical and practical training to provide basic knowledge needed to operate without automation assistance. Some of the performance objectives of this training phase could be, for example: checking and using the working position equipment, using approved phraseology, applying prescribed procedures or appreciating priority of actions, among others.

Rating Training: Theoretical and practical specific knowledge related to the rating in which will be trained, Area Control Surveillance in case of AUTOPACE project scope. Some of the objectives performance of this phase could be: demonstrate the ability to manage air traffic without ATC System assistance, handle complex and dense traffic situations or apply the corresponding procedures to area control surveillance.

Automation Training: Practical knowledge focused on the acquisition of Technical Competences within the automated framework, that is, with the ATC System assistance.

Psychological Training will be an innovative training phase which will be divided into two parts:

Psychological Cognitive Training: Specific training phase to cope with the development of Psychological Cognitive Competences, especially those related with Comprehension and Projection.

Psychological Non-Cognitive Training: Focused on Psychological Non-Cognitive Competences. Will be based on techniques for coping with stress in order to respond to any potential challenging situation, as well as to improve the identification of symptoms of lack of situational awareness (biofeedback technique).

The evaluation to ensure the ATCo has acquired (or has not lost) the future competences (technical and psychological) will be carried out through the called ATCo Performance Monitoring. This methodology will be used to identify if a controller has suffered a significant loss of competences along the Training Program and he/she needs Refresh Training to recover the appropriate and safe level of competences.

Further Research on Training Strategies

RA#8: Validation on the use of ATCO Model as a reference for the ATCo Trainee: The ATCo Psychological Model chases to behave as an “ideal” and an ordinary future ATCo since it represents the cognitive processes expected for an ATCo in the 2050 environment considering the relevant tasks and responsibilities necessary to cope with the expected traffic forecasts keeping an acceptable MWL level. The model could be used not only for checking system features suitability but also to support a training design plan. The final goal for the ATCo trainee would be to manage the traffic within acceptable MWL levels as the model does (always assuming that the ATCo Psychological Model is calibrated). The Model would be calibrated for every training phases and the trainee target would be to behave as the model does.


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RA#9: Development of platforms to simulate exercises for the different degrees of automation: AUTOPACE proposes that training on a simulator is the most important phase to acquire the technical and psychological competences. The main risks due to high automation are related to system failures (non-nominal situations) and therefore the more exhaustive training covering all possible failures modes can be done on a simulator. On the Job-Training and Refresh Trainings are still necessary for acquiring the Air Traffic Controller license and maintaining ATCo competences but the development of platforms to emulate different levels of automation and failure become essential to prepare future ATCos to be ready to recover back control.

RA#10: Validation of specific exercises to acquire technical and psychological competences: AUTOPACE has proposed a catalogue of training techniques and strategies to acquire technical and psychological competences. Specific exercises have been proposed to design exercises according to different phases of complexity (basic, intermediate, advanced, consolidation) in case of technical and psychological cognitive training. Validation is required to check their feasibility and suitability.

RA#11: Validation of psychological non-cognitive training strategies such as biofeedback techniques, questioners on line among others: Biofeedback is a technique in which one or more psychophysiological parameters (heart rate, respiratory rate, brain waves ...) are recorded using sensors placed in different parts of the body. These registers are automatically displayed on screens to be scanned by the ATCos trainees. The hypothesis is to say that it is possible to train the ATCo to identify and to relate body signals to high or low levels of activation. In addition to Biofeedback techniques, another technique to keep the correct level of activation consists of questions about the system performance appearing randomly in the screen during the provision of Air Traffic Control to detect a wrong system behavior. These techniques are proposed in AUTOPACE for validation.

RA#12: Research on how assess and monitor ATCo performance during ATCo psychological training: Following with the previous research area, it is necessary to research on how the psychological competences (cognitive and non-cognitive) are already acquired. The identification of the right measure to estimate objectively the mental workload that the ATCo has, the level of activation or the stress that the ATCo is feeling is key to determine if the ATCo has acquire the right competences to safely manage the air traffic in high automated environments.

Safety and Risk Assessment (for details see ppt attached)

AUTOPACE Preliminary Hazard Assessment (PHA) conducts safety assessment aiming to provide a set of automation risks that should be mitigated by modifying ATCo training or refining the automation design. This PHA is executed in two cycles. In the first cycle, for the defined AUTOPACE Concept of Operations (ConOps) and nominal scenarios and non-nominal situations, PHA i.e. hazard identification and risk assessment have been performed and critical hazards are identified (those with high and unacceptable risk). Initial set of risk mitigation measures that should be used in the definition of competences and training requirements as a guideline to refine them, are defined (for the given set of critical hazards). The same approach has been used in the second cycle of PHA taking into account the modified competence and training requirements proposed in AUTOPACE. Issues identified in the second cycle served to further refine competences and training requirements in order to mitigate critical safety issues remained.

Hazard Identification processes have been done through brainstorming sessions with operational experts identifying hazards relevant for the particular scenario/situation in general (operations specific, general hazards), while other hazards are task specific (task specific hazards). Risk


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Assessment is based on the severity and likelihood to each hazard. Value of severity and likelihood associated to hazards are very important as they indicate whether and how decreasing severity, likelihood, or both of them, can reduce risk levels, specifically for those hazards which can be mitigated through future ATCo training. Those are hazards related to ATCo performance, reduced SA due to boredom/fatigue/overload/too much information shown/tunnelling, human errors - slips/lapses/ mistakes/violations, etc.

Using a first catalogue of training strategies, some critical hazards disappear, some are categorized as acceptable/tolerable after decreasing their severity, likelihood or both, some remain critical with lower risk (from unacceptable to high risk) and some remain unchanged. These last ones are related to new procedures or system features that cannot be solved just with training.

Further Research on Safety and Risk Assessment

RA#13: Research on new system features and new operational procedures where training does not mitigate critical hazards: In certain categories of hazards improvements can be expected to achieve through training, insufficient or no improvements can be expected to achieve through training. Although some of those hazards are related to ATCo performances (mainly Incorrect action category), majority are related to other components of the system (equipment, procedures and environment). It is recommended to further research on these kind of mitigation activities to complete the safety assessment in high automation environments.

RA#14: Third (Fourth, etc.) cycle analysis – accounting more details about system architecture, i.e. details on equipment and tools: AUTOPACE has performed two cycles of preliminary hazard assessment. Main inputs for Risk assessment have future tasks (performed by ATCo or ATC system) and AUTOPACE system description. Once the Concept of Operation is refined, new cycles are proposed to refine these preliminary assessments by considering details on equipment, tools, technical and psychological training, roles and responsibilities and different nominal and no-nominal situations.

RA#15: Further improvements of Safety Assessment approach steps: The Safety Assessment approach consists of three steps (Hazard identification, Risk assessment and Risk matrices). Hazard Identification based on brainstorming is proposed to be improved to ensure a systematic identification of hazards. In turn, the risk assessment needs a stronger connection between mental workload model and severity/likelihood. And finally, the risk matrices have mathematical and logical limitations to be amended.

RA#16: Development of new methodology for Safety Assessment of future ATM: The best available methodologies which exist today and used in AUTOPACE are ICAO’s and EUROCONTROL’s methodologies. They are commonly used for safety assessment not only of the current system, but also of the future systems (no matter how far that future is – it is important to have a notion the system definition). Anyway, it is worthy research on new methodologies or adaptation of current ones to be applied in high automation environments at long term phase as the level of uncertainty is high and the methodology suitability could be improved for those cases.


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Prioritization of Research Areas

Based on the set of Research Areas proposed by AUTOPACE, the second part of the workshop dealt with the prioritization of these areas. For the accomplishment of this objective, the session was organised in two parts:

Part I – Working in Groups

The audience was divided in five groups. Firstly, every participant was invited individually to write the three most important research areas to be further analysed giving arguments for his/her selection. Some examples of the individual task are shown in Annex A.

Secondly, by using coloured stickers with different punctuations, the participants showed their interest on the common picture of AUTOPACE proposed research areas. By ranking the areas according to the ones obtaining the highest punctuation, the group achieved a consolidated three most priority research areas. Internal discussion at group allowed consolidating and coordinating common arguments to defend the selection of these three research areas afterwards.

The results of the three most relevant research areas for every group can be found in Annex B.

Part II – Working All Together

During the second part of the session, every group shared the most priority research areas. In a first round, every group spoke up the most priority Research Area providing the corresponding ARGUMENTS. If any of the other four groups found COUNTER-ARGUMENTS to the proposed research area, they were encouraged to speak them up. The project coordinator stuck green cards on the proposed Research Area on the poster and red cards for those areas with Counter-Arguments.

Once all groups had spoken, a second and a third rounds occurred with the next priority Research Areas according to their group ranks providing ARGUMENTS. Again, all groups were encouraged to propose COUNTER-ARGUMENTS.

The group with fewer Counter-Arguments was the winner of this Game. The following picture reflects the results of this part of the session.


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Results of the prioritization

The Research Areas identified as highest priority are:

RA#1: Future ATC System Development (4 ARGUMENTS): The Concept of Operation is the frame of future challenges providing a holistic view of the solution under validation. The function allocation between System and ATCo is essential to better understand his/her future ATCo responsibilities, the direction of system development and the potential levels of automation. The concept of operation is the area where the other research areas lay on since human factor aspects, training strategies and safety assessment need for details to ensure proper analyses and research. The extension of the definition of a Concept of Operation not only for the en-route phase but also TMA and Airports is necessary. The definition of different non-nominal situations (RA#4: Definition of different non-nominal scenarios-2 ARGUMENTS) is strongly related and complimentary to this area. The identification of potential non-nominal situations makes the ATM system more resilient and therefore less dependent to malfunctions. Hazards will be better identified and therefore safety assessment will provide more robust mitigation actions.

RA#9: Development of platforms to simulate exercises for the different degrees of automation (3 ARGUMENTS): The simulation and therefore the validation of different levels of automation require adequate platforms to prove the new concepts, design training, develop operational procedures and identify the positive and negative impact of different levels of automation on ATCo work. New platforms need to be developed in order to provide several good automated system identifying challenges. In turn, as full automation will not be implemented in one step but requires transition, platforms are the means to test the automatized system features. Different non-nominal situations can exhaustively studied in these platforms to train ATCos to safely recover control and design supporting tools to bridge human weaknesses.

RA#2: Definition of different non-nominal scenarios (2 ARGUMENTS): The definition of different non-nominal scenarios apart of the ones presented is a topic has to ve investigated deeply. A research on the unfortunately consequences and their impact on the ATCo has to be analysed as well as the transition for him/her during the transition period from nominal to non-nominal situations.

RA#5: Validate the combination effect of automation on the level of activation (overconfidence, fears of automation) in simulated environments (1 ARGUMENT): This is the key aspect to be researched for the analysis on how automation is impacting on human, the ATCo. The system can only be further developed once known the abilities and capabilities of the ATCo operating in high automated systems. To do so it is necessary to validate the contradictory effects of automation on ATCo trust on the system (overconfidence or fears of automation). System and training requirements are complementary areas to support ATCo competences acquisition and maintenance.

RA#7: Research on ATCo supporting tools design to boost the use of required cognitive processes (comprehension and projection) affected by future automation (1 ARGUMENT): As the ATCo role in high automation scenarios is changing to monitoring and supervising roles, his/her cognitive demands will be oriented to understand the situation. New tools to improve his/her brain power use on comprehension and projection are desirable to make decisions if necessary to recover control in case of failure.


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RA#10: Validation of specific exercises to acquire technical and psychological competences (1 ARGUMENT): Exercises design to ensure the competence acquisition is relevant for training strategy validation. The design of specific training plan to address not only the technical aspects but also the psychological ones becomes essential to prepare ATCo for all potential hazards. The validation of the training exercises is necessary to check their effectiveness.

RA#12: Research on how assess and monitor ATCo performance during ATCo psychological training (1 ARGUMENT): To provide the ATCo Performance Monitoring, it is desirable that a methodology will be defined as well as its assessment during ATCo psychological training. The research on operational readiness and continuous update of the information in view of the future complex dynamic environments has also to be assured to know how the psychological competences (cognitive and non-cognitive) will be acquired.

RA#15: Further improvements of Safety Assessment approach steps (1 ARGUMENT): A new Safety Assessment approach considering not only the Hazard identification, Risk Assessment and Risk matrices but also the new requirements and steps to cover the new system has to be evaluated. The research on safety impact on a high automated system should be highly considered and not be overlooked.

RA#16: Development of new methodology for Safety Assessment of future ATM (1 ARGUMENT): Following with the previous research area, the updating of the safety models considering future investigation on equipment, tools, technical and psychological training, roles and responsibilities and different nominal and no-nominal situations should be a priority to ensure the development of future ATM including a correct harmonisation and the regulation in the system.

As it is shown in the previous section the above research areas received also contra-arguments:

RA#1: Future ATC System Development (3 CONTRA-ARGUMENTS) and RA#9: Development of platforms to simulate exercises for the different degrees of automation (1 CONTRA-ARGUMENTS) are the research areas that received more arguments but also contra-arguments. This is due to the prioritisation. Some groups thought that the main research areas that has to be developed is the ATC system environment, however the other groups thought that before the system, it is necessary to define the platform to reach the desired grade of automatism. This is the reason why some groups indicated these research areas with some arguments and contra-arguments.

RA#2: Definition of different non-nominal scenarios, RA#5: Validate the combination effect of automation on the level of activation (overconfidence, fears of automation) in simulated environments and RA#12: Research on how assess and monitor ATCo performance during ATCo psychological training received also 1 contra-argument due to the order in the prioritisation of the research areas.

It is remarkable that even though safety and risk assessment areas receive few arguments none contra-argument was given to them (RA#15: Further improvements of Safety Assessment approach steps and RA#16: Development of new methodology for Safety Assessment of future ATM). The same happens with the ATCo psychological model research area (RA#7: Research on ATCo supporting tools design to boost the use of required cognitive processes (comprehension and projection) affected by future automation) and with the competence and training research area


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(RA#10: Validation of specific exercises to acquire technical and psychological competences) which did not receive any contra-argument.


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Annex A - Individual Research Areas

Annex A collects some examples obtained from the first Workshop activity #4 Game: Prioritization of Research Areas (Individual Task).


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Annex B - Research Areas per group

Annex B collects some examples obtained from the Workshop activity #4 Game: Prioritization of Research Areas. The pictures below show the three most priority research areas consolidated per group.


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[title of publication] - autopaceautopace.eu/.../2017/12/20171127_autopace-minutes_worksho… ·...

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