A B S T R A C TWe investigated the possibility of developing a decision support system (DSS) that integrates eye-fixation measurements to better adapt its suggestions. Indeed, eye fixation give insight into human decision-making: Individuals tend to pay more attention to key information in line with their upcoming selection. Thus, eyefixation measures can help the DSS to better capture the context that determines user decisions. Twenty-two participants performed a simplified Air Traffic Control (ATC) simulation in which they had to decide to accept or to modify route suggestions according to specific parameter values displayed on the screen. Decisions and fixation times on each parameter were recorded. The user fixation times were used by an algorithm to estimate the utility of each parameter for its decision. Immediately after this training phase, the algorithm generated new route suggestions under two conditions: 1) Taking into account the participant's decisions, 2) Taking into account the participant's decisions plus their visual behavior using the measurements of dwell times on displayed parameters. Results showed that system suggestions were more accurate than the base system when taking into account the participant's decisions, and even more accurate using their dwell times. Capturing the crucial information for the decision using the eye tracker accelerated the DSS learning phase, and thus helped to further enhance the accuracy of consecutive suggestions. Moreover, exploratory eye-tracking analysis reflected two different stages of the decision-making process, with longer dwell times on relevant parameters (i.e. involved in a rule) during the entire decision time course, and frequency of fixations on these relevant parameters that increased, especially during the last fixations prior to the decision. Consequently, future DSS integrating eyetracking data should pay specific care to the final fixations prior to the decision. In general, our results emphasize the potential interest of eye-tracking to enhance and accelerate system adaptation to user preference, knowledge, and expertise.

Figure 1. GazeForm concept. Left: when eye-hand coordination exists for touch modality the surface is flat. Right: when the gaze is solicited by another task the surface offers a salient tangible control allowing continuity of manipulation and freeing the gaze.

OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in: http://oatao.univ-toulouse.fr/ Eprints ID: 16193 Evaluating future technology concepts for air traffic control ground operations requires exploration of work scenarios of differing complexities, i.e. scenarios that create more or less taskload for air traffic controllers. While the link between traffic load and workload has been well-characterized in the literature and is often the only complexity variable applied to validation studies, there are other operational events that can augment controller workload. Through a series of interviews and on-site observations of professional and student air traffic controllers, we defined seven general operational events that can be applied to all airport ground operations. We discuss the development of two scenarios of different workloads (average and hard) and their validation with air traffic controllers. INTRODUCTIONIn addition to augmenting the number of aircraft in the air space, the forecasted growth of air traffic also increases the number of ground movements at busy airports (Eurocontrol, 2013), adding increased collision risk, time delays, pollution, and stress for the air traffic control (ATC) officer (ATCO). As feasible solutions are explored, most of which involve the inclusion of ground automation and in-cockpit or in-tower technology, it is important to ensure that such solutions are robust to the ATCO's workload. Therefore, work scenarios of different workloads (i.e., taskloads) and complexities must be designed and evaluated. In particular, it is important to characterize the different sources of complexities for the tower ATCO. Much has been written in the literature regarding link between workload and traffic load, visibility, and tool utility, but less has been discussed regarding operational events. Such events can be used individually or in combination depending on project aims and the general experience of the participant body. Furthermore, the majority of the work done in this field has focused on air traffic management en route and not on the ground. This paper describes the general operational events that can contribute to scenario complexity specifically for the ground (GND) ATCO. We begin with a review of current literature regarding scenario complexity in tower ATC operations. Next, the general methodology is described, including the demographics of the persons interviewed and observed. The first half of this paper concludes with a definition of the seven operational events that can be used to increase taskload complexity of the GND controller. The second half of the paper introduces two scenarios, Average and Hard, that were developed for the evaluation of modern taxiing techniques and ends with the scenario validation and concluding thoughts.

Project Modern Taxiing (MoTa) studies the impact of future taxiing technologies such as Datalink and autonomous taxiing tugs on airport taxiing operations and air traffic controller workload. Seven air traffic controllers were asked to manage ground traffic in two scenarios that imposed medium and high levels of workload with three different degrees of automated technology assistance: paper strips; Datalink and path suggestion; Datalink, path suggestion, and tugs. Initial results indicate that participants were able to manage more traffic when using either just the interface or interface and tugs, but the inclusion of tugs also resulted in an increase in self-reported workload. Participants were divided on technology acceptance with no one rejecting completely the new technology.

The expected growth in air traffic has resulted in many projects attempting to mitigate the problem of air traffic control, particularly at airports. These projects have focused on characterizing the workload of the air traffic control officer and/or introducing automated technology to assist in his or her responsibilities. Many of these projects have used existing simulation facilities and technology or developed analogous environments to simulate the air traffic control tower. However, such high-fidelity simulation facilities are in limited locations or not easily accessible. Results gathered in simplified environments, while accurate in a controlled setting, may be limited in their extrapolation to real-world applications. Furthermore, little guidance is provided in the literature for developing an ATC tower micro-world, particularly in terms of knowing which elements are most necessary to simulate and the most effective way to actualize such functions. In this paper, we present the development of an air traffic control tower simulator, specifically for the ground controller, intended for the design and validation of potential automated concepts. We discuss our reasoning for the simulation of specific elements, the hardware and the software used, and our methodology for simulating ATC operations within the tower. This paper concludes with lessons learned and results from the simulation validation, a novel 10-question 5-point Likert scale questionnaire.