HF in Future ATM

HF in Future ATM

Air Traffic ControllerThe world of Air Traffic Management is on the threshold of major changes. Europe and the United States have launched large-scale innovation programmes like SESAR and NextGen. The implementation of new technologies, operational concepts and collaborative decision making processes have to improve the efficiency of the Air Traffic Management (ATM) system. These developments will have their impacts on the future work and competences of air traffic controllers. The Human Factors (HF) in Future ATM programme researches the effects that the changing ATM system has on the required competences of air traffic controllers.k

The challenge

The main objectives of the research program are: (1) to gain insight in how changes in technologies, operational concepts, and the coordination of the aviation chain affect competences required at the organisational and individual level of air traffic management (ATM); (2) to design flexible models for training that are based on the new competences and responsive to the underlying changes. This also requires a deeper understanding of the organisational factors that either facilitate or block the conversion of external changes into policies for training and selection; (3) to optimise selection models and tools for future controller selection. These three main objectives are depicted in the diagram below: 

General_framework

Project descriptions

Program Approach: The different projects start from the following general model that has been chosen as general framework for the KDC HF research program ‘human factors in future air traffic management’. The general idea is that innovations in technologies, operational concepts and forms of coordination in the aviation chain can lead to alternative ways of organizing the ATM system, that is, to define and allocate the system’s functions to its various technical and human components, and that these options will influence the future work and expertise of ATCOs and other operational personnel. Of central importance throughout the project are critical competences. Apart from their significance for safe and effective performance, these competences are also important for assessing the feasibility and costs of selection and training. Two important changes in ATM competences are expected to occur in ‘shared mental models’ and ‘cognitive flexibility’.verwachten in de projecten ‘Shared Mental Models’ en in de ‘Cognitive Flexibility’.

Planning

Organisation & Competences: This project ‘Organization & competences in future ATM’ investigates future developments in ATM from a human factors (HF) perspective. Human factors can be defined as follows: ‘Human factors is about giving the human operator an efficient working environment and tools which take account of human strengths and limitations, but it is also about selecting the most suitable operators and giving them the required skills’ (Kirwan et al, 1997). An HF-perspective in ATM, as a counterpart of technology, is based on the assumption that human factors are critical for any ATM system, because the system’s intended operation will always be dependent on human capabilities, learning, safety, etcetera and will be constrained by possibilities to recruit, select and train people with the requisite personal qualities.

Organisation__competences

Failure to consider HF at the stage of design of a new ATM system may pose a threat to its ultimate effectiveness and safety. Although the aforementioned projects all pay attention to human factor issues, a uniform conceptual framework and methodology are still lacking. There is also a lack of organized knowledge about essential facts and relationships. It is described what ‘should be done’ on HF-issues in ATM research, but a follow-up on these notes is lacking. Moreover, the HF information described in various documents (e.g., SESAR, NextGen) is fragmented, incomplete and inconsistent, also because HF is considered from many different perspectives and expertises. There is an apparent need to incorporate HF in ATM system design in a consistent way, to specify HF requirements, and to develop a set of design principles and guidelines.  

This project aims to determine how HF input in ATM system design can be structured in such a way that it helps to make choices in design alternatives and to evaluate the various options systematically. Starting point is the open and uncertain future of aviation. Although certain developments may seem likely today, the actual developments can differ from expectations, and current operational concepts in ATM have many uncertainties. For instance, we don’t know yet exactly how the task allocation between ATCOs and pilots will look like and which support tools will be used.
This project ‘Organization & competences in future ATM’ uses a number of key concepts that are defined in the following ways.

Scenarios: A scenario (or: ATM scenario) is defined as a hypothetical description of a series of interrelated events that represent a possible future development and state of the ATM system. It is based on a set of assumptions regarding system components, the way in which they interrelate, and the environment in which the system is embedded and it entails a comprehensive view of the system as a whole, including technologies, operational concepts and forms of organization.

Organizational models: An organizational model is defined as a representation of an organizational entity that consists of people and systems, the functions it fulfils in its environment, the structure by which it differentiates and integrates roles and activities, and the operational and control processes carried out.

Job roles: Job roles are defined as descriptions of the activities to be performed by people occupying certain positions as spelled out by the organizational model. They reflect how work is divided and how it is supposed to fit together.

Competences: Competence is defined as ‘the ability to effectively apply acquired knowledge, skills and attitudes while performing tasks in realistic settings’.

controller

Cognitive flexibility: This PhD-project will deliver insight in factors that are relevant in terms of cognitive flexibility. Cognitive flexibility refers to the ability to deal with unforeseen changes in the environment (task). At the one hand this refers to individual characteristics (cognitive capability), but on the other hand it also addresses environmental issues, like the task, equipment and so on, that may enhance and facilitate people to deal with those changes. For instance, the changes need to be noticed before operators can deal with these changes. And how information is presented or communicated affects whether an event will be noticed, and also how people will respond to it. Therefore this project will focus on changes in tasks that are unexpected or unforeseen, and peoples’ response to these changes will be studied.
The objective is formulate recommendations for training and selection systems for people that are frequently dealing with unforeseen changes, and also to look at task and system design aspects that may help operators.

The job of an air traffic controller (ATCO) is very complex, and requires a high level of cognitive skills. An important task requirement for ATCOs is that they have to be able to respond immediately when there is an unforeseen event, for example an emergency or system failure, but also during daily operation unforeseen events occur frequently (runway closure, weather circumstances, etc). The ability to effectively react to unforeseen changes in the work has been called adaptability or cognitive flexibility.

Recent developments in air traffic management suggest that cognitive flexibility might become even more important in the future, in particular when the current trend of increasing number of aircrafts to be handled continues. ATCOs have an active role in communicating and directing pilots, in fact they are handling aircraft on an individual basis. When the number of aircrafts to be handled increases, as is foreseen in various scenarios, ATCOs are likely to rely more on computer guided systems. Although ATCOs will remain responsible for directing aircraft safely to the airport, the strategies they use to do this might change. ATCOs will probably rely more frequently on automatic data transmission systems. For safety reasons, however, in the future ATCOs will still need to be able to intervene when systems fail. In these, presumably rare, occurrences, ATCOs need to be able to recognize a failure and be able to immediately switch to an active role.

In this research project, it will be investigated how people react to unforeseen changes and what factors are related to cognitive flexibility. In a series of studies, we will specifically focus on investigating cognitive and environmental antecedents of successful reactions to unforeseen changes in the context of complex on-time decision making tasks mirroring task demands in ATC. The project will provide recommendations regarding the design of ATM systems and (cognitive) requirements for training and selection of ATCOs.

Communication in teams; Shared Mental Models: Air traffic control is a very dynamic and complex team task which requires a high degree of coordination and information exchange. Foreseen changes in Air Traffic Management of the next decades will result in more automation, pre-flight planning and electronic communication. This novel situation increasingly requires controllers to anticipate information requirements and meet team and task demands in circumstances when time demands are high.

SMM_framework

Shared mental models enable a team to take appropriate actions and fulfil teammates’ needs by ensuring a common understanding of the task and team. Therefore, the current research explored shared mental models of air traffic controllers which have been shown to contribute to efficient team performance. To meet these growing task demands, team members need accurate shared knowledge about each others’ task, also referred to as Shared Mental Models (SMMs). SMMs enable a team to take appropriate actions and fulfil teammates’ needs by ensuring a common understanding of task and team aspects. The present PhD-project focuses on SMM of ATCOs by means of three main goals:

  1. Defining shared mental models of ATCOs
  2. Studying the process and effects of sharing mental models
  3. Back to practice: implications for efficient teamwork in future Air Traffic Management 

Self_directed_learningSelf-directed Learning in Adaptive Training Systems: This PhD-project will focus on the question how a flexible training system for ATC (Initial Training) can be developed that makes it possible to meet the individual learning needs of trainees by shifting responsibility to the trainees in such a way that they become more and more self-directed learners, and are able to monitor and assess task performance, and select learning tasks that fulfil their learning needs.

The focus of the project will be on a training philosophy, based on further developments of current training methods and will use the existing learning tasks (that is simulator training tasks and part task practices) and the current portfolio (LIS) as a starting point, but will also anticipate on future competences needed in various (unforeseeable) situations. The project will build on the current innovations in ATC. That is, it will use the available standards and criteria for assessment, the assessment system and the coaching protocols. The project aims at developing general design guidelines for flexible training, especially concerning SDL in dynamic task selection.

Outreach: Professional environments such as Air Traffic Control are characterized by increasing interdependency and complexity. As the complexity of the situation and environment increases, it becomes more unlikely that an individual will be able to manage the situation alone. Therefore, organizations are increasingly using teams to handle difficult, complex situations.

Many studies on effective team performance show that effective teams have developed specific team behaviours such as supporting each other, re-allocating tasks to share workload, taking initiative, and providing relevant information to other team members. Such behaviours rely on team members having an adequate awareness of other team member’s performance and workload. Similarly, we expect that for effective team learning in a collaborative environment, it is essential to be able to adequately assess one’s own and other team members’ learning progress and share workload. In recent years, the interest in cognitive strategies such as self-monitoring and self-regulation in cognitive and learning research has grown considerably.

Adequate self-monitoring is important, especially in self-directed learning programs, because it determines the effort and time an individual spends on learning something or taking extra measures so as to prevent forgetting. However, these cognitive strategies, such as Judgments of Learning, have mainly been studied in individual learning environments. Therefore, this study aims to investigate how adequate judgments of learning can be supported in a collaborative learning environment and whether these contribute to individual and team learning.

Results

The results will contribute to design and optimise the ATM system from a human factor point of view. Moreover, they may also help to solve the existing shortage of air traffic controllers at LVNL (and other ANSPs) in two ways: (1) by improving selection and training, and; (2) simplification of the human role in the ATM-system in spite of increasing traffic. The results will also be applicable in other parts of the aviation chain due to changing interactions between the various parties involved and similarities in roles and competences. Different results an deliverables will be available during various phases of the projects. Available deliverables will be downloadable at the bottom of this site.

Involved parties

LVNL, KLM, AAS, NLR, TU-Delft, Open University, University of Maastricht.

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