Abstract

International audience; In this paper we review the activities of Air Tra c Control and Management (ATC/M) and expose scenarios that illustrate current and future challenges in this domain. In particular we look at those challenges that can be tackled with the use of immersion. We introduce the concepts of an immersive Remote Tower and Collaborative Immersive Trajectory analysis. These make use of immersive technologies such as Head Mounted Displays (HMDs) or large, tiled displays to immerse users in their tasks, better supporting the management and analysis of the complex data produced in this domain

Abstract

International audience; The International Civil Aviation Organisation (ICAO) identify an Airprox to be a situation in which, in the opinion of a pilot or air traffic services personnel, the distance between aircraft as well as their relative positions and speed have been such that the safety of the aircraft involved may have been compromised. These are relatively rare events but they must be reported and investigated in order to reduce future risks. Airprox investigations and similar studies into near-miss incidents focus on the risk to passengers and crew. They do not consider the impact of debris. This raises concerns when, for example, the Bijlmermeer crash led to the deaths of 39 people on the ground. This paper presents a system that was developed to simulate the risks from aircraft debris on ground-based infrastructures. The system was developed and validated with help from Airprox investigators. To this end, a User Centered Design process was applied; analysing the activities and needs of potential users from two European investigation agencies. The following pages present the key design decisions, provide insights into the development process and identify limitations with our existing system. The closing sections identify further applications of this approach and suggest areas for further work.

Abstract

International audience; The main goal of Data Mining is the research of relevant information from a huge volume of data. It is generally achieved either by automatic algorithms or by the visual exploration of data. Thanks to algorithms, an exhaustive set of patterns matching specific measures can be found. But the volume of extracted information can be greater than the volume of initial data. Visual Data Mining allows the specialist to focus on a specific area of data that may describe interesting patterns. However, it is often limited by the difficulty to deal with a great number of multi dimensional data. In this paper, we propose to mix an automatic and a manual method, by driving the automatic extraction using a data scatter plot visualization. This visualization affects the number of rules found and their construction. We illustrate our method on two databases. The first describes one month French air traffic and the second stems from 2012 KDD Cup database.

Abstract

International audience; During their initial and on-the-job training, air traffic controllers communicate with human operators called pseudo-pilots who act as pilots for several simulated aircraft. With the expected increase in air traffic, a significantly higher number of aircraft will be handled during the simulations. The existing tools and working methods of the pseudo-pilots do not allow them to handle more traffic without increasing the number of operators. The increase in the number of pseudo-pilots induces problems of cost, logistics and collaboration (distribution of traffic and radio frequency congestion). This article describes the design process and improvement of a pseudo-pilot HMI which led us to a radical change of both the visualization and the interaction. This user centered process aims to optimize visualization, effectiveness of interaction and the level of realism of the simulations. We also integrated in a seamless and robust way voice recognition in the visualization.