The introduction of 4-D trajectory-based operations will require the development of new and more advanced "humancentered" decision support tools for future air traffic controllers. One approach to the design of human-centered decision aids is ecological interface design, which focuses on visualizing the boundaries of safe system performance rather than prescribing predetermined strategies or discrete solutions. Previous studies with ecological interfaces in the aviation domain revealed that humans sometimes opted for control actions close to these boundaries, giving rise to a general concern about the robustness of control actions. The goal of this study has been to empirically investigate how effectively an ecological interface for 4-D trajectory management, as developed in a previous study, supports the preservation of airspace robustness. For this purpose, a metric has been developed to evaluate both minimum and average sector-based and control-based robustness. Special attention was paid to quantifying and measuring the effect of expertise level on the robustness of human-generated control actions. Results of a human-in-the-loop experiment indicate that expert participants were most robust in their control actions, as compared with either skilled or novice participants. This result suggests that boundary-seeking control actions with ecological interfaces are mainly dependent on the level of expertise and the control strategies of the end user.Index Terms-Air traffic management, automation, control space robustness, ecological interface design, human-machine interaction.

It is to be expected that the task of an air traffic controller will change with the introduction of four-dimensional (space and time) trajectories for aircraft, as can be seen in ongoing developments in ATM systems in Europe (SESAR) and the US (NextGen). It is clear that higher levels of automation will need to be developed to support the management of four-dimensional trajectories, but a definite concept on a distribution of the roles of automation and human users has not yet been well defined. This paper presents one approach to the design of a shared representation for 4D trajectory management. The design is based on the Cognitive Systems Engineering framework and by using a formative approach in the analysis of the work domain, a step-wise refinement in the planning and execution of 4D trajectories is proposed. The design is described in three Abstraction Hierarchies, one for each phase in the refinement. The ultimate goal is to design a shared representation that underlies both the design of the human-machine interface and the rationale that guides the automation. It is foreseen that such a shared representation will greatly benefit the shared cognition in ATM and allows shifting back and forth across various levels of automation. A preliminary version of a joint cognitive system for 4D trajectory management has been developed and will be introduced in this paper. Further work will focus on the refinement of the shared representation by means of human-in-the-loop experiments.

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In the coming decades, the task of an air traffic controller is expected to shift to one of strategic, trajectorybased air traffic management. This form of air traffic control is no longer possible without the help of automated support tools. In previous research, it has been shown that the time-space diagram, combined with a conventional plan view display is a good candidate for supporting an air traffic controller with the inbound planning task in the future situation. However, in this initial study, the vertical plane was not yet fully included. Secondly, during an initial validation experiment, creating and maintaining a 'mental picture' of the traffic was reported to be a difficult task. These findings lead to the re-design of the interface in the current research, which focuses on implementing the vertical plane and improving the integration of information across the successive displays. An experiment has been performed with a PC-based simulation which validates that the enhanced interface can be used to manage the air traffic safely and efficiently. Secondly, it has been shown that the ability to manipulate the speed of an aircraft in the adjacent sector can significantly increase situation awareness and reduce controller workload.

In the near future, air traffic controllers are expected to adhere to stringent time and position constraints in controlling traffic. For this new task, new decision-support tools are required which include higher levels of automation, whilst letting humans remain to be the ultimate responsible for the safety of operations. In previous research, an advanced human-machine interface was designed and evaluated that allows controllers to manipulate four-dimensional flight plans of each individual aircraft. In this research, a higher level of automation is explored by designing a new interface prototype that enables controllers to manipulate multiple flows of traffic by facilitating interaction with a path-planning algorithm. A first evaluation of this interface, in which five participants were asked to structure a perturbed airspace as they saw fit, showed that the participants were able to influence the algorithm as they desired and were supported by the interface that visualized the inner workings of the algorithm. However, human influence did not improve the solutions in terms of sector robustness and efficiency, as compared the previously designed interface for aircraft. Therefore, improvements and its use case warrant further research.