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Our work aims to explore novel approaches to the challenge of designing the interaction between people and automation. Through a case study within the domain of air traffic control, we focus on designing fine-grained human–automation interactions. We design a concept and develop an interactive lo-fi prototype of an assisted sketching system to enable air traffic controllers to interact with automation in a fine-grained manner and to externalize mental images. Assisted sketching seems to offer a possible way to communicate different degrees of predictive certainty using visual cues and interaction. Our insights further suggest that externalization through assisted sketching could encourage exploration of future scenarios, and support communication and collaboration between air traffic controllers and between air traffic controllers and pilots. The explorative benefits for the individual decision-making process might be more evident in situations where air traffic controllers have more time for reflection, for example during planning or debriefing and in educational settings. [ABSTRACT FROM AUTHOR]

Interaction with automated systems and other types of technologies seems inevitable and almost a requirement of human work. The aviation sector, and in particular air traffic control, is devoting considerable efforts towards automation, to respond to the increased demand for capacity. Project AUTOPACE investigated the impacts of foreseeable automation over human performance and behaviour. The purpose was to identify new training requirements for air traffic controllers under foreseeable automation scenarios. In addition to the research carried out under the remit of AUTOPACE, the functional resonance analysis method was used to explore how the interactions between human operators and technology may change, as new automation features would be introduced into ATC operations. The FRAM model was developed based on AUTOPACE concept of operations, two levels of automation (E2 and E1) and was then used to instantiate three different non-nominal situations that were also investigated by the project. This paper presents the FRAM-based analysis carried out and discusses the potential impacts of automation, considering uncertainty and variability as two critical aspects that emerge from complex operation scenarios. The relation with AUTOPACE work is continuously established and the added value of FRAM for the pursuit of further AUTOPACE work is argued. [ABSTRACT FROM AUTHOR]

Air traffic controllers must maintain a consistently high level of human performance in order to maintain flight safety and efficiency. In current control environments, performance-influencing factors such as workload, fatigue and situation awareness can co-occur and interact to affect performance. However, multifactor influences and the association with performance are under-researched. This study utilised a high-fidelity, human-in-the-loop, en route air traffic control simulation to investigate the relationship between workload, situation awareness and controller performance. The current study aimed to replicate Edwards et al.'s (in: Proceedings of the 4th AHFE international conference, 21-25th July, San Francisco, USA, 2012) previous finding that factors known to be associated with controller performance do co-vary and can interact, which is associated with a compound influence on performance. In addition, the current study aimed to extend Edwards et al.'s (2012) study by engaging retired controllers as participants and comparing multifactor relationships across four levels of automation. Results suggest that workload and situation awareness may interact to produce a compound (as opposed to cumulative) impact on controller performance. In addition, the effect of the interaction on performance may be dependent on the context and level of automation. Findings have implications for human-automation teaming in air traffic control, and the potential prediction of performance-influencing situations, supporting controller performance in the operational environment. [ABSTRACT FROM AUTHOR]

Future air traffic control will have to rely on more advanced automation to support human controllers in their job of safely handling increased traffic volumes. A prerequisite for the success of such automation is that the data driving it are reliable. Current technology, however, still warrants human supervision in coping with (data) uncertainties and consequently in judging the quality and validity of machine decisions. In this study, ecological interface design was used to assist controllers in fault diagnosis of automated advice, using a prototype ecological interface (called the solution space diagram) for tactical conflict detection and resolution in the horizontal plane. Results from a human-in-the-loop simulation, in which sixteen participants were tasked with monitoring automation and intervening whenever required or desired, revealed a significant improvement in fault detection and diagnosis in a complex traffic scenario. Additionally, the experiment also exposed interesting interaction patterns between the participants and the advisory system, which seemed unrelated to the fault diagnosis task. Here, the explicit means-ends links appeared to have affected participants' control strategy, which was geared toward taking over control from automation, regardless of the fault condition. This result suggests that in realizing effective human-automation teamwork, finding the right balance between offering more insight (e.g., through ecological interfaces) and striving for compliance with single (machine) advice is an avenue worth exploring further. [ABSTRACT FROM AUTHOR]

The management of uncertainty is a critical aspect of current as well as future air traffic control operations. This study investigated: (1) sources of uncertainty in enroute air traffic control, (2) strategies that air traffic controllers adopt to cope with uncertainty, (3) the trade-offs and contingencies that influences the adoption of these uncertainties, and (4) the requirements for system design that support controllers in following these strategies. The data were collected using a field study in two enroute air traffic control centres, involving 'over the shoulder' observation sessions, discussions with air traffic controllers, and document analysis. Three types of uncertainty coping strategies were identified: reducing uncertainty, acknowledging uncertainty, and increasing uncertainty. The RAWFS heuristic (Lipshitz and Strauss in Organ Behav Hum Decis Process 69:149-163, 1997) and anticipatory thinking (Klein et al. in Anticipatory thinking, Proceedings of the eighth international NDM conference, Pacific Grove, CA, 2007) were used to identify reduction and acknowledgement strategies. Recent suggestions by Grote (Saf Sci 71:71-79, 2015) were used to further explore strategies that increase uncertainty. The study presents a new framework for the classification of uncertainties in enroute air traffic control and identified the uncertainty management strategies and underlying tactics, in context of contingencies and trade-offs between operational goals. The results showed that controllers, in addition to reducing and acknowledging uncertainty, may deliberately increase uncertainty in order to increase flexibility for other actors in the system to meet their operational goals. The study describes new tactics for acknowledging and increasing uncertainty. The findings were summarized in the air traffic controller complexity and uncertainty management model. Additionally, the results bring to light system design recommendations that allow controllers to follow these different coping strategies, including (1) the design of alerts, (2) the transparency of prediction tools, and (3) system flexibility as a requirement for acknowledging and increasing uncertainty. The results are particularly important as uncertainty is likely to increase in future operations of enroute air traffic control, requiring automation support for controllers. Implications for future air traffic management scenarios as envisioned within the SESAR Joint Undertaking (SESAR JU in European ATM Master Plan, 2 eds, 2012) and NextGen (FAA in FAA's NextGen implementation plan, 2014) operational concepts are discussed. [ABSTRACT FROM AUTHOR]