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EEG-based performance estimation during a realistic drone piloting task
No full textInternational audiencePassive brain-computer interfaces (pBCIs) developed within the neuroergonomic field usually aim to improve safety by augmenting human-machine interaction. To accomplish said goal, many pBCIs classify mental states such as mental workload or mental fatigue. An alternative is to forego mental states and aim to predict performance. Despite its drawbacks, we argue that performance estimation is a more goal-oriented approach than mental state estimation. In a realistic experiment, 25 participants had to control an uncrewed aerial system for two hours, continuously switching between target search and navigation. EEG classification accuracies based on mental states and performance were compared. With a Tangent Space Logistic Regression, we could predict an increased likelihood of lapses in the form of missing instructions with an above-chance level accuracy of 62.09 %
Study of the Frequency Dispersion of 3D-Printed Dielectric Crystals for Dielectric Resonator Antenna Applications
No full textInternational audienceIn this paper, the study of simple cubic (SC) and face-centered cubic (FCC) crystals, in addition to the use of the plane wave expansion method allows us to understand the dispersive behavior of electrically-large unit cells. From numerical analyzes, we demonstrate that we can take this dispersive behavior into account for the design of a dielectric resonator antenna (DRA) made up of electrically-large 3D-printed SC unit cells
Text-Enriched Air Traffic Flow Modeling and Prediction Using Transformers
No full textInternational audienceThe air traffic control paradigm is shifting from sector-based operations to flow-centric approaches to overcome sectors’ geographical limits. Modeling and predicting intersecting air traffic flows can assist controllers in flow coordination under the flow-centric paradigm. This paper proposes a flow-centric framework – TEMPT: Text-Enriched air traffic flow Modeling and Prediction using Transformers – to identify, represent, and predict intersecting flows in the airspace. Firstly, nominal flow intersections (NFI) are identified through hierarchical clustering of flight trajectory intersections. A flow pattern consistency-based graph analytics approach is proposed to determine the number of NFIs. Secondly, in contrast to the traditional traffic flow feature representation, i.e., numerical time series of flights, this paper proposes a text-enriched flow feature representation to intuitively describe the “flow of flights” in the airspace. More specifically, air traffic flow features are described by a “text paragraph” composed of the time and flight sequences transiting through the NFIs. Finally, a transformer neural network model is adopted to learn the text-enriched flow features and predict the future traffic demand at the NFIs during future time windows. An experimental study was carried out in French airspace to validate the efficacy of TEMPT using one-month ADS-B data in December 2019. Prediction results show that TEMPT outperforms the competitive air traffic flow modeling and prediction approaches: time-series-based Transformers, Long Short-term Memory (LSTM), and Graph Convolutional Networks (GCN), as well as aerodynamic trajectory simulation-based prediction and the historical average
Rethinking LEO Constellations Routing
No full textInternational audienceThis study investigates the Unsplittable Multi-Commodity Flow (UMCF) as a routing algorithm forLEO constellations. Usually, LEO routing schemes enable the Floyd-Warshall algorithm (Shortest Path)to minimize the end-to-end latency of the flows crossing the constellation. We propose to solve the UMCFproblem associated with the system as a solution for routing over LEO. We use a heuristic algorithmbased on randomized rounding known in the optimization literature to efficiently solve the UMCF problem.Furthermore, we explore the impact of choosing the first/last hop before entering/exiting the constellation.Using network simulation over Telesat constellation, we show that UMCF maximizes the end-to-end linksusage, providing better routing while minimizing the delay and the congestion level, which is an issue todayover new megaconstellations. Keywords:LEO constellations, routing, Floyd-Warshall, UMCF, Hypatia,ns3 simulato
Air-rail timetable synchronization: Improving passenger connections in Europe within and across transportation modes
No full textInternational audienceThis study addresses the integration of the railway and airline scheduling problems, in order to offer passengers smooth transfers between rail and air. This paper focuses on optimizing the air and rail timetables at 18 major European airports including three hubs and their associated train stations. A multimodal passenger demand simulation, using constraint programming and based on real data, is proposed. Six days in December 2019 are analyzed, and ten simulations per day are performed. These instances are publicly released. The air-rail timetable synchronization is applied to these 60 simulated days. Three scenarios are tested in which each operator agrees to change its schedule or not. Results show that changing only 13% of European flights by 11 minutes on average could increase the number of suitable connections for passengers by 60%. In addition, if both airlines and railway operators adapt their schedules, passenger comfort is improved and operator costs are reduced, even more so than with unilateral changes
Évaluation Scientifique de l'Augmentation de l'Age de Départ à la Retraite sur les Fonctions Cognitives et le Bien-être des Contrôleurs Aériens
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AI Automation for Transmission Electron Microscope Alignment
No full textInternational audienceTransmission electron microscopes, like other scientific instruments, are becoming increasingly complicated. Consider the I2TEM in Toulouse, a dedicated TEM for electron holography and in-situ research (HF-3300 C from Hitachi) which has a cold-field emission gun, 9 lenses, 4 apertures, 3 biprisms, 18 pivot points to align, and nearly as many elements in the corrector. Operation involves more than one hundred configurable parameters, but with approximately 10300 theoretically possible configurations, one wonders if the instrument is used to its full potential. Furthermore, appropriate microscope alignment takes between twenty minutes and an hour each day, depending on the experiment and the microscopist’s effectiveness. We propose to explore the use of artificial intelligence to automate the alignment, therefore tackling the complexity and reducing the time taken by the task
Considerations for Handover and Co-working with Drones
No full textInternational audienceRecent progress in aerial robotics foresees that flying robots, a.k.a. drones, can support workers in their jobs, such as by performing complex tasks in hard-to-reach places. As they become increasingly autonomous, we envision co-working drones helping human operators in direct collaborative tasks, such as by carrying tools and handing them over to workers at heights, or helping them lift and precisely position structures on construction sites. Yet, much research is needed to support safe close-body interaction between humans and drones. We here propose specific considerations for human-drone collaboration related to such handover, from the drone approaching a person in view of interacting with them at close proximity, to the handover itself, and to the drone leaving. In addition, we present the results of semi-structured interviews with three professionals in this context of human-drone collaboration. This late-breaking report highlights challenges and opportunities fostered by Human-Aerial Robot Handover (HARH)
Status quo and challenges in air transport management research
No full textInternational audienceAir transport management research, concerned with all facets of aviation operations, policies, and strategies, is an essential element of making our aviation system more sustainable and preparing it for the challenges inherentto the present and future. Based on a data-driven categorization of almost 2,000 papers published on the subject, we discuss the status quo in air transport management research. Through our data-driven categorization we have identified 15 broad topics. For each topic, we provide a description of the state of the art and propose 2-3 challenges, respectively. Overall, our study provides a set of 35 challenges to the research community. Accordingly, we hope and believe that our study makes a valuable contribution, mainly by guiding the air transport management research community towards a delineated work plan on the research landscape of air transport as well as the present challenges, ultimately helping to improve the global air transport system
A heuristic-based multi-objective flight schedule generation framework for airline connectivity optimisation in bank structure: An empirical study on Air China in Chengdu
No full textInternational audienceAs the first step of airline schedule planning, flight scheduling plays a pivotal role in shaping an airline’s competitiveness, defining its profitability and establishing service levels by determining the timetable for potential city pairs. Although full-service carriers consider the bank structure as an effective method to improve flight connectivity and optimise aircraft utilisation, existing literature lacks models specially focused on optimising flight schedules within the bank structure. This paper effectively addresses the existing gap by proposing an integrated multi-objective flight scheduling model to optimise airline connectivity in bank structure. The generalised formulation allows airlines to maximise their connectivity while controlling the traffic flow during flight scheduling, offering more flexibility to adjust parameters according to their specific needs. By formulating the problem as an integrated tail-dependent one, this study measures the impact of aircraft routing decisions on the set of feasible flight pairings continuously. Further, a novel heuristic-based Selective Simulated Annealing (SSA) algorithm is designed to implement and solve the proposed model promptly. Computational results demonstrate the applicability and effectiveness of the proposed approach, revealing that the systematic consideration of flight interactions leads to significant improvements in airline connectivity and aircraft utilisation. Notably, in test instances for over 200 daily flights, the proposed approach yields a solution that significantly increases airline connectivity by 18.58% while respecting the operational constraints. Validated with historical flight schedule data, the resolution approach serves as an efficient data-driven decision-making tool, which enables airlines to respond to the fast-changing air transportation market dynamics in real-time. In addition, this paper discusses and concludes with managerial insights regarding bank length verification and flight schedule optimisation