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Very-low-level U-space Conflict Detection and Resolution: Focused Developments, Analysis, and Future Prospects
No full textInternational audienceA safe and efficient integration of U-space operations necessitates robust conflict detection and resolution (CD&R) mechanisms, particularly for very-low-level (VLL) operations in constrained urban airspace. Research has focused on the development of navigation and traffic management concepts suitable for such operations that aim to mitigate the challenges posed by this novel environment. However, the current research landscape is fragmented, with CD&R methods still needing to be integrated within a more unified framework. In this paper, we present an overview of our approach towards air traffic management for VLL U-space operations and analyse their limitations compared to other work. Then, based on the conclusions of other existing work, we identify key areas for improvement and propose recommendations for future research and development for VLL airspace structure design, conflict detection and resolution, and U-space operations simulations. We conclude that a unified approach should be used towards integrating and investigating the interdependencies of U-space services within a standardised verification and validation framework
Reactive Semantics for User Interface Description Languages
No full textInternational audienceUser Interface Description Languages (UIDLs) are high-level languages that facilitate the development of Human-Machine Interfaces, such as Graphical User Interface (GUI) applications. They usually provide first-class primitives to specify how the program reacts to an external event (user input, network message), and how data flows through the program. Although these domain-specific languages are now widely used to implement safety-critical GUIs, little work has been invested in their formalization and verification. In this paper, we propose a denotational semantic model for a core reactive UIDL, Smalite, which we argue is expressive enough to encode constructs from more realistic languages. This preliminary work may be used as a stepping stone to produce a formally verified compiler for UIDLs
Drone assistant pour personnes avec déficiences visuelles
No full textInternational audienceNavigation in unfamiliar environments represents one of the most significant challenges for people with visual impairments (PVI). This affects their autonomy and their ability to participate in daily life activities, such as shopping. To address this issue, we studied where and how a drone can be used as a spatial assistant to complement primary mobility aids such as white canes or guide dogs. We designed an assistive drone through a participatory design process including interviews, focus groups, and simulated Wizard-of-Oz deployments with 21 PVI participants. We concluded this study with expert feedback to validate our co-design. Our results revealed key design elements for an assistive drone, notably the importance of voice guidance, adaptable interaction modes ("Team" and "Explorer" modes), and the need for seamless integration with existing assistive technologies. Our work contributes to the growing field of assistive technologies by detailing the needs and preferences of users for assistive drones, paving the way for the development of more usable solutions that augment, rather than replace, primary mobility aids.La navigation dans des environnements inconnus représente un des défis les plus importants pour les personnes avec déficiences visuelles (PDV). Cela affecte leur autonomie et leur capacité à participer aux activités de la vie quotidienne, telles que faire les courses. Pour répondre à cette problématique, nous avons étudié où et comment un drone peut être utilisé en tant qu'assistant spatial en complément des aides primaires d'assistance à la mobilité telles que la canne blanche ou le chien-guide. Nous avons conçu un drone d'assistance à travers un processus de conception participative comprenant des interviews, des groupes de discussion et des déploiements simulés de type Magicien d'Oz avec 21 participants PDV. Nous avons terminé cette étude avec le retour d'experts pour valider notre co-conception. Nos résultats ont révélé des éléments clés en matière de conception pour un drone assistant, notamment l'importance du guidage vocal, des modes d'interaction adaptables (modes Équipe et Explorateur), et la nécessité d'une intégration transparente avec les technologies d'assistance existantes. Notre travail contribue au domaine en pleine croissance des technologies d'assistance en détaillant les besoins et les préférences des utilisateurs pour les drones d'assistance, ouvrant la voie au développement de solutions plus utilisables qui viennent augmenter, plutôt que remplacer, les aides primaires à la mobilité
Apprentissages complexes : mieux comprendre la gestion des ressources cognitives pour aider les apprenants
No full textLes travaux ont pour objectif une meilleure compréhension de l’acquisition d’habiletés et de compétences complexes en situations écologiques. Ils sont centrés sur trois déterminants de ces apprentissages : (1) les caractéristiques des apprenants, (2) l’efficience dans la gestion des ressources cognitives en situation de multitâche et (3) l’influence de divers outils pédagogiques fournissant un feedback correctif et un guidage attentionnel. La plupart des travaux a été réalisée dans le domaine de l’aviation (pilotage et contrôle aérien) et peut s’appliquer à des thématiques de sélection et de formation. Les perspectives de recherche envisagées ont pour visée une meilleure compréhension des habiletés à gérer des ressources cognitives et de leur acquisition. Il s’agira notamment de tester diverses interventions pédagogiques visant à favoriser l’acquisition de stratégies efficientes de gestion des ressources
Spectral Analysis of Delay Propagation in Air-Rail Intermodal Networks
No full textInternational audienceIntermodal transportation networks integrating airand rail systems are critical for efficient and sustainable pas-senger mobility, yet their performance is often challenged bycascading disruptions originating from delays at key hubs. Thispaper presents a novel application of Graph Signal Processing(GSP) techniques to analyze delay propagation and characterizeunexpected disruptions within a large-scale air-rail intermodalnetwork. Using real flight data and simulated rail delay data forthe Paris Charles de Gaulle (CDG) hub, we model the networkof transportation legs as a graph where edges represent Pearsoncorrelation coefficients of delay patterns. We introduce spectralmetrics such as total variation and total energy derived fromthe graph Laplacian to quantify the spatial smoothness andirregularity of delay distributions. The spectral decompositionvia the Graph Fourier Transform (GFT) enables identificationof distinct delay patterns associated with both expected andirregular states of the network. Our results reveal that, while mostdays exhibit smooth and predictable delay propagation consistentwith historical correlations, select days demonstrate significantlyhigh total variation, indicating unexpected disruption dynamics.This methodological framework provides transport operatorswith actionable insights to detect, characterize, and potentiallymitigate complex disruption scenarios in multimodal hubs
Investigating the Independent and Combined Effects of Startle and Surprise in a Simulated Flight Task
No full textInternational audienceObjective We aimed to characterize the impact of startle and surprise, both independently and in combination, on subjective feelings, behavior (task performance and gaze behavior), and several physiological parameters. Background The effects of startle and surprise are known to affect pilots’ cognitive performance, with potential impact on safety. Startle and surprise can occur either together or independently, yet no studies have experimentally distinguished their specific effects. Method Participants ( n = 45) were each assigned to one of the three conditions while performing the MATB-II task. In the startle condition, participants were subjected to an expected loud sound. In the surprise condition, an unexpected reverse video effect was applied to the experimental interface. In the combination condition, participants were exposed to both stimuli simultaneously. Results Surprise was associated with an increase in skin conductance without affecting performance. In contrast, startle was marked by a decline in performance on the communication sub-task, increased skin conductance and heart rate, and a narrowing of attention. When startle and surprise were combined, the results mirrored those of startle alone but included a stronger feeling of startle and surprise, and a more prolonged heart rate increase. Conclusion Startle and surprise combined yielded more numerous significant effects on subjective, behavioral, and physiological measures than startle and surprise independently. Application Identifying the specific impacts of startle and surprise could pave the way for their automatic detection using artificial intelligence. Safety could be enhanced through the design of specific countermeasures to help the crew cope with such states
Data-Driven Arrival Trajectory Optimization Model Based on Improved Genetic Algorithm
No full textInternational audienceTrajectory optimization is essential for realizing trajectory-based operation and has become a hot topic in air traffic management research in recent years. Although existing optimization models have significantly succeeded in their applications, most still need controllers to intervene during rush hours. To further improve the trajectory optimization performance, this paper proposed a data-driven-based trajectory optimization model that learns human controllers’ experience from historical data and embeds this knowledge into the trajectory optimization model to enhance its performance. Case studies at Guangzhou Baiyun International Airport are conducted to validate the proposed model. Compared with a conventional genetic-algorithm-based trajectory optimization model, the proposed approach—by incorporating real historical trajectory data—demonstrates significantly improved performance in managing arrival flows during peak hours, increasing airspace capacity by approximately 30% under trajectory-based operation conditions. Besides, the optimized trajectories embedded with more actual operation experience are familiar to controllers and pilots; therefore, the airspace user training cost would be relatively low
Schedule optimization and staff allocation for airport security checkpoints using guided simulated annealing and integer linear programming
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Closed-form Expression for the Radiation of an Arbitrarily-Oriented Stochastic Elementary Dipole
No full textInternational audienceAntenna systems subjected to uncertainties need tobe characterized considering variability in their parameters or intheir environment. This paper presents a two-step methodologybased on spin spherical harmonics and polynomial chaos expan-sions to assess the statistics of the radiated electric field. It isapplied to derive the closed-form expression for the radiation ofan arbitrarily-oriented stochastic elementary dipole, constitutinga first validation of the methodology, which allows for exactestimation of the field probability density function
Enhancing Airport Ground Operations Efficiency through Speed-Controlled Aircraft Taxiing and Future Guidance Readiness
No full textInternational audienceThis paper presents a speed-controlled aircraft taxiing optimisation approach designed to improve airport surface operations by strategically managing ground movements. The proposed method integrates a sliding window-based decomposition strategy to dynamically resolve conflicts, enabling real-time adaptability to fluctuating traffic conditions. Operationally, the approach prioritises minimising holding point delays over pushback delays to promote smoother flow and better gate utilisation.Simulation results at Paris Charles de Gaulle (CDG) Airport demonstrate that the algorithm significantly reduces average delays, with many flights requiring no holding or pushback adjustments. Even during peak periods, the system maintains low average taxiing, holding, and pushback times, highlighting its robustness under congested conditions. In addition to enhancing current operational efficiency, the proposed speed control framework establishes a foundation for future innovations, such as the implementation of follow-me vehicles to guide aircraft during taxiing, further improving safety, predictability, and sustainability in airport ground operations