Cognitive Support

Topic description

Specific Challenge:

According to the SESAR vision outlined in the European ATM Maser Plan, advancing the automation in ATM is the key to significant performance improvements across many aspects of ATM and development and implementation of higher levels of automation will enable handling the predicted increase in air traffic demand and contribute significantly to achieving the SES High-Level Goals.

The ATM system is currently designed to rely upon relatively high levels of human intervention to manage the air traffic safely and efficiently. This role of the human is being challenged and it is expected to change towards more of a supervisory role yet also maintaining the human as a critical and an integral element of the ATM system. Experience from ATM and other domains shows that increased dependence on automation makes it important to consider automation failure scenarios, system resilience and the challenge of maintaining a skilled and competent workforce. There will be a need to assess the human performance issues for ATC in a similar way to those that are known to affect flight-crew performance in the glass cockpit. These include the need to prevent the risks associated to moving the human operator into a monitoring role: stress, lack of attention, loss of situational awareness and de-skilling.

A promising approach to preventing these issues is to progressively evolve the ATM system into a Joint Human Machine Cognitive System following an integrated design that optimises the collaboration of actors in view of optimising system performance. Development and implementation of higher levels of automation will require careful consideration of the strength of human and automation systems as well as the identification of new human roles in parallel with the development of ATM concepts and use of technology.

Proposals for research in this area should target an ATM system with a medium to high level of automation in which the human operator is working cooperatively with advanced automation as a digital assistant. Both, ATM-related airborne and ground systems are in scope.

Research may address human performance aspects related to higher levels of automation (i.e. stress, lack of attention, de-skilling, complacency…) and resilience, e.g. by developing new approaches for defining suitable task allocation strategies enabling a cooperation of ATCOs and/or other ATM actors and automation. This may include the use of adaptable or adaptive automation concepts. Projects may in particular focus on potentially required hand-overs between automated systems and human operators as well as handovers between human-human and machine-machine in normal and degraded modes of operation. These new approaches may build upon the existing legacy and SESAR solutions in the pipeline, or they could take a clean-sheet approach to automation. These proposals should validate the proposed design of ATM systems automation, focusing of expected future roles and procedures. They may consider approaches focusing on the front-end of automation and using a human to operate the automation in the background (e.g. Wizard-of-Oz approach) or even use a predefined reaction of the automation.

Proposals may also address the implications of the expected future role of the human and the foreseen introduction of new support tools on training requirements and develop appropriate training concepts. Projects are encouraged to take into consideration the opportunities enabled by the current advancement of technology for the design and delivery of training.

Proposals may also focus on specific aspects of these new systems. For example, proposals may investigate the application of psychophysiological measurements like neurometrics or the detection of facial expressions for applications like stress management systems, fatigue declaration, new training techniques or adaptive automation. Proposals may also consider to investigate potential application of activity trackers available on the consumer market. Proposals planning to investigate the application of psychophysiological measurements need to propose a specific application within the ATM system.

Proposals addressing this topic should not only consider normal operating situations but also take into account system failures and degraded modes of operation. This requires identification of system failure states and definition of appropriate procedures.

Proposal addressing this topic should take into consideration the results of SESAR WP-E projects, in particular HALA!, and ER1 projects (AUTOPACE, MINIMA, STRESS). Under this topic, there is also substantial scope for learning from other transportation modes and other industries and it is expected that proposals will build upon an established body of knowledge and apply this into the challenges of ATM.

The concepts for Joint Cognitive Human Machine systems and/or innovative Training concepts developed in these research are expected to enlarge the body of knowledge that is needed to make it possible to safely introduce higher levels of automation in ATM, which should provide substantial benefits for capacity and cost-effectiveness, safety and security of ATM operations.