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Imaginer le futur des conférences en IHM - le cas de ParaCHI
No full textInternational audienceThe COVID-19 pandemic has forced academic conferences to move online. This paradigm shift from 'one-venue conferences' is also, and above all, necessary for reasons of sustainability and inclusivity. ACM SIGCHI is moving in this direction by offering hybrid conferences and allowing satellite events such as ParaCHI. However, alternative conference formats are rarely discussed in terms of their indirect effects, i.e., the changes in behavior and practices they induce, which can have consequences not only for the environment but also for research. In this article, we present the results of a survey on the direct and indirect effects of ParaCHI Paris 2025, as well as the findings of a workshop organized during this conference on scenarios for future conferences.La pandémie de COVID-19 a contraint les conférences scientifiques à se dérouler en ligne. Ce changement de paradigme des « conférences sur un seul site » est aussi et surtout nécessaire pour des raisons de soutenabilité et d'inclusivité. ACM SIGCHI évolue en ce sens en proposant des conférences hybrides et en autorisant les événements satellites tels que ParaCHI. Cependant, les formats alternatifs de conférence sont rarement discutés en termes d'effets indirects, c'est-à-dire les changements de comportement et de pratiques qu'ils induisent, qui peuvent avoir des conséquences non seulement sur l'environnement, mais aussi sur la recherche. Dans cet article, nous présentons les résultats d'une enquête sur les effets directs et indirects de ParaCHI Paris 2025, ainsi que les réflexions d'un atelier organisé pendant cette conférence sur les scénarios pour les futures conférences
Évaluation des performances des méta-signaux GNSS en environnement multitrajets
No full textInternational audienceGlobal Navigation Satellite Systems (GNSS) are fundamental for positioning, navigation, and timing (PNT), playing a crucial role in next-generation intelligent transportation systems and safety-critical applications. However, achieving precise PNT solutions in challenging environments remains a significant challenge. Under ideal conditions, carrier-phase-based techniques such as Real-Time Kinematics (RTK) and Precise Point Positioning (PPP) enable high-precision positioning. However, their accuracy heavily depends on the quality of phase observables, which can be degraded in harsh environments, such as urban canyons or interference-prone scenarios. A promising alternative is the use of large-bandwidth signals, which enhance resolution and improve code-based observables. This can be achieved through high-order Binary Offset Carrier modulations or GNSS meta-signals. This study investigates the fundamental performance limits of time delay and Doppler estimation for such signals in challenging scenarios, particularly in the presence of multipath interference, where signal reflections significantly impact receiver performance. Characterizing multipath effects is critical for the next generation of PNT applications, as it directly influences the robustness of GNSS solutions. To analyze these effects, we derive the Cramér-Rao Lower Bound (CRB) for time-delay and Doppler estimation under a signal model where one specular multipath degrades GNSS receiver performance. This case considers that the receiver is aware of the multipath and applies countermeasures. In the second case, we assume that the receiver is unaware of the multipath, for which we derive the Misspecified CRB (MCRB). The MCRB quantifies the performance degradation in standard GNSS receivers due to unmodeled multipath interference. We validate these theoretical bounds by comparing them with state-of-the-art estimation algorithms. Our results demonstrate the significant performance improvements achievable in harsh conditions using metasignals such as Galileo E5a + E5b or GPS L2 CM + L5, compared to legacy signals such as GPS L1 C / A.Les systèmes mondiaux de navigation par satellite (GNSS) sont essentiels pour le positionnement, la navigation et le temps (PNT), et jouent un rôle crucial dans les systèmes de transport intelligents de nouvelle génération ainsi que dans les applications critiques pour la sécurité. Toutefois, obtenir des solutions PNT précises dans des environnements difficiles demeure un défi majeur. Dans des conditions idéales, les techniques basées sur la phase de la porteuse, telles que la cinématique en temps réel (RTK) et le positionnement ponctuel précis (PPP), permettent un positionnement de haute précision. Cependant, leur exactitude dépend fortement de la qualité des observables de phase, qui peuvent être dégradées dans des environnements contraints, tels que les canyons urbains ou les scénarios sujets aux interférences.Une alternative prometteuse réside dans l’utilisation de signaux à large bande passante, qui améliorent la résolution et renforcent la qualité des observables de code. Cela peut être réalisé grâce aux modulations Binary Offset Carrier d’ordre élevé ou aux méta-signaux GNSS. Cette étude examine les limites fondamentales de performance de l’estimation du retard temporel et de l’effet Doppler pour de tels signaux dans des environnements contraignants, en particulier en présence d’interférences dues au multitrajet, où les réflexions du signal affectent considérablement les performances du récepteur. La caractérisation des effets du multitrajet est déterminante pour la prochaine génération d’applications PNT, car elle influence directement la robustesse des solutions GNSS.Pour analyser ces effets, nous dérivons la borne inférieure de Cramér-Rao (CRB) pour l’estimation du retard et de l’effet Doppler dans un modèle de signal où un multitrajet spéculaire dégrade les performances du récepteur GNSS. Ce premier cas considère que le récepteur est conscient de la présence du multitrajet et applique des contre-mesures. Dans un second cas, nous supposons que le récepteur ignore le multitrajet ; nous en déduisons alors la borne de Cramér-Rao sous spécification erronée (MCRB). La MCRB permet de quantifier la dégradation des performances des récepteurs GNSS standards due au multitrajet non modélisé.Nous validons ces bornes théoriques en les comparant avec des algorithmes d’estimation de pointe. Nos résultats démontrent les améliorations de performance significatives qu’il est possible d’obtenir dans des conditions difficiles grâce aux méta-signaux, tels que Galileo E5a + E5b ou GPS L2 CM + L5, par rapport aux signaux historiques tels que GPS L1 C/A
Functional ecological inference
No full textNational audienceIn this paper, we consider the problem of ecological inference when one observes the conditional distributions of Y|W and Z|W from aggregate data and attempts to infer the conditional distribution of Y|Z without observing Y and Z in the same sample. First, we show that this problem can be transformed into a linear equation involving operators for which, under suitable regularity assumptions, least squares solutions are available. We then propose the use of the least squares solution with the minimum Hilbert–Schmidt norm, which, in our context, can be structurally interpreted as the solution with minimum dependence between Y and Z. Interestingly, in the case where the conditioning variable W is discrete and belongs to a finite set, such as the labels of units/groups/cities, the solution of this minimal dependence has a closed form. In the more general case, we use a regularization scheme and show the convergence of our proposed estimator. A numerical evaluation of our procedure is proposed
Modified Dijkstra’s Algorithm for Search and Rescue Operations in Dynamic Wildfire Environments
No full textInternational audienceWhile the increasing frequency and severity of wildfires highlight the urgent need for innovative and efficient response strategies, Unmanned Aerial Vehicles (UAVs) are increasingly recognised as valuable assets in Search and Rescue (SAR) operations, particularly in natural disaster scenarios. This paper presents a novel approach that leverages a coordinated UAV team to guide inhabitants to safe locations in wildfireaffected areas. The proposed framework determines the optimal sequence of the locations for UAVs to follow by computing the fastest safe path, while considering real-world complexities, such as road conditions for evacuees and the dynamic spread of wildfires, to maximise the survival rate of rescues. To address this problem, an innovative algorithm that integrates a metaheuristic method with a modified Dijkstra's algorithm is specifically designed for dynamic environments. The effectiveness of the proposed algorithm is validated with a preliminary test.</div
Impact du Leurrage sur le Traitement du Signal d'un Récepteur GNSS
No full textRadio Frequency Interference (RFI), such as jamming and spoofing, represents a growing threat to GNSS receivers, especially in civil aviation, which requires a high level of accuracy, integrity, continuity, and availability. Although jamming and spoofing interference signal models have been extensively studied in the literature, and GNSS observables are commonly used in spoofing detection, the exact impact of spoofing on these observables remains relatively unexplored.Understanding the impact of jamming and spoofing on GNSS receivers is essential for enhancing their resilience and facilitating the development of more sophisticated detection methods. Developing a model of the receiver’s signal processing under jamming and spoofing conditions could enable the characterization and bounding of the impact of these threats on GNSS receivers. Furthermore, such a model would help identify different jamming and spoofing threats based on the interplay between the receiver, satellite, and spoofer geometries, as well as the receiver's configuration.To this end, this thesis aims to characterize the impact of RFI on GNSS receiver signal processing both before and after correlation.First, this thesis investigates the impact of chirp jamming and spoofing interference on the Intermediate Frequency (IF) signal and Automatic Gain Control (AGC). Prior to correlation, the spoofing signal acts as a jamming signal for the receiver, beginning to impact the receiver at a power level comparable to the noise floor. The spoofing impact on AGC fluctuates by several decibels depending on the spoofing parameters, but tends to approximate a Gaussian process as the number of interfering signals increases.Next, the thesis characterizes the impact of spoofing on GNSS receivers after correlation by modeling the correlator output, tracking loop behavior, and C/N0 estimator under spoofing interference. The spoofing impact after correlation can be categorized into four distinct situations: nominal, induced-jamming, induced-spoofing, and induced-multipath. This study reveals complex and potentially harmful distortions, particularly in the induced-multipath situation, where the receivers encounter very significant and unpredictable distortion. This includes significant C/N0 distortions along with non-linear and chaotic behaviors in tracking loops, inducing potential loss-of-lock, synchronization bifurcation, cycle slips, and high tracking errors.Les interférences radiofréquences (RFI), telles que le brouillage et le leurrage, représentent une menace croissante pour les récepteurs GNSS, en particulier dans l'aviation civile, qui nécessite un haut niveau de précision, d'intégrité, de continuité et de disponibilité. Bien que les modèles de signaux d'interférences de brouillage et de leurrage soient largement étudiés dans la littérature, et que les observables GNSS soient couramment utilisées pour les détecter, l'impact exact du leurrage sur ces observables reste relativement inexploré.Comprendre l'impact du brouillage et du leurrage sur les récepteurs GNSS est essentiel pour améliorer leur résilience et faciliter le développement de méthodes de détection plus sophistiquées. Développer un modèle du traitement du signal du récepteur en présence de brouillage et de leurrage pourrait permettre de caractériser et de délimiter l'impact de ces menaces sur les récepteurs GNSS. En outre, un tel modèle aiderait à identifier les différentes menaces de brouillage et de leurrage en fonction de l'interaction entre le récepteur, le satellite et la géométrie du leurre, ainsi que la configuration du récepteur.Dans cette optique, cette thèse a pour objectif de caractériser l'impact du brouillage et du leurrage sur le traitement du signal GNSS, tant aux étapes précédant que suivant la corrélation.Tout d'abord, cette thèse étudie l'impact du brouillage par chirp et du leurrage sur les statistiques du signal reçu et sur le contrôle automatique du gain (AGC). Avant la corrélation, le signal de leurrage agit comme un signal de brouillage pour le récepteur, commençant à affecter le récepteur à un niveau de puissance comparable à celui du bruit de fond. L'impact du leurrage sur l'AGC fluctue de plusieurs décibels en fonction des paramètres du leurrage, mais tend à approcher un processus gaussien à mesure que le nombre de signaux de leurrage augmente.Ensuite, la thèse caractérise l'impact du leurrage sur les étapes de réception après corrélation en modélisant la sortie du corrélateur, le comportement de la boucle de suivi et l'estimateur de C/N0 en présence de leurrage. L'impact du leurrage après corrélation peut être catégorisé en quatre situations distinctes : nominal, brouillage-induit, leurrage-induit et multitrajet-induit. Cette étude révèle des distorsions complexes et inquiétantes, en particulier dans la situation de multitrajet-induit, où les récepteurs rencontrent des distorsions très significatives et imprévisibles. Cela inclut de fortes distorsions du C/N0, ainsi que des comportements non linéaires et chaotiques dans les boucles de poursuite, induisant des pertes de poursuite, des bifurcations, des sauts de cycle et des erreurs de pseudodistance importantes
Cyclists route choice modeling from trip duration data in urban areas
No full textThe lack of GPS data limits the ability to reconstruct the actual routes taken by cyclists in urban areas. This article introduces an inference method based solely on trip durations and origin-destination pairs from bike-sharing system (BSS) users. Travel time distributions are modeled using log-normal mixture models, allowing us to identify the presence of distinct behaviors. The approach is applied to 3.8 million trips recorded in 2022 in the Toulouse metropolitan area, with observed durations compared against travel times estimated by OpenStreetMap (OSM). Results show that, for many station pairs, trip durations align closely with the fastest route suggested by OSM, reflecting a dominant and routine practice. In other cases, mixture models reveal more heterogeneous behaviors, including longer trips, detours, or intermediate stops. This approach highlights both the stability and diversity of cycling practices, providing a robust tool for usage analysis in data-limited contexts, and offering new insights into urban mobility dynamics without relying on spatially explicit data
GNSS performance degradation under meaconing in civil aviation: pseudorange and position models
No full textInternational audienceWith the escalating prevalence of in-band interference, the vulnerability of Global Navigation Satellite System (GNSS) receivers to potential jamming or spoofing threats has become a critical concern. The proliferation of GNSS repeaters, commonly known as meaconers (electronic devices that intercept GNSS signals, amplify them, and subsequently rebroadcast them) contributes to this threat landscape, by compromising GNSS accuracy, availability, continuity, and integrity. Specifically, the performance of standardized aviation receivers might be degraded when exposed to meaconing interference, causing critical yet unknown safety issues. This study assesses the robustness against meaconing, by evaluating the behavior of the checks performed by a certified aviation receiver. Firstly, the precise mathematical models of the GNSS observables (code, phase, smoothed pseudoranges, and carrier-to-noise density ratio C / N 0 ) are derived under meaconing interference. Secondly, this study evaluates the robustness of the aviation consistency tests performed on the pseudoranges in the presence of meaconing. Thirdly, this paper classifies the meaconer impacts at the position level, to analyze in each situation the robustness brought by the fault detection test. Finally, the effects of meaconing on the accuracy, the availability, and the integrity of the estimated positions are presented for each situation. It is shown that a meaconer deteriorates the accuracy and availability, and marginally increases the probability of misleading position information. This comprehensive analysis contributes to better understand the risks associated with meaconing signals and paves the path to a global assessment of the meaconer impact during an approach phase of flight, integrating piloting considerations
Full Pose Tracking via Robust Control for Over-Actuated Multirotors
No full textInternational audience— This paper presents a robust cascaded controlarchitecture for over-actuated multirotors. It extends the Incremental Nonlinear Dynamic Inversion (INDI) control, combined with structured H∞ control—originally proposed forunder-actuated multirotors in [12]—to a broader range ofmultirotor configurations. Furthermore, it reduces the controllaw’s dependency on the multirotor model compared to themethods in the literature by shifting it to the actuator model,thereby improving the closed-loop robustness to uncertainties.To achieve attitude and position tracking, we employ a weightedleast-squares geometric guidance control allocation method,formulated as a quadratic optimization problem, enabling fullpose tracking. The proposed approach effectively addresseskey challenges, such as preventing infeasible pose references,enhancing robustness to disturbances, and accounting for themultirotor’s actual physical limitations. Numerical simulationswith an over-actuated hexacopter validate the method’s effectiveness, demonstrating its adaptability to diverse missionscenarios and its potential for real-world aerial applications
Extracting aircraft conflict-resolution situations from historical ADS-B data
No full textInternational audienceExisting conflict resolution models are often based on theoretical frameworks that, while providing optimal solutions under specific criteria, may not fully align with real-world controller decision-making practices. This gap between model predictions and actual behaviour can lead to low acceptance of automated tools. Understanding how controllers resolve conflicts in daily operations could help design assistance tools that generate advisories more likely to be accepted and integrated into their workflow. This study introduces a data-driven methodology for identifying and cataloguing air traffic deconfliction instances using historical ADS-B data. By analysing trajectory deviations and their impact on predicted aircraft separations, we extract instances of deconfliction and encode them into a structured dataset. This dataset captures key elements of each event, including sector information, deviated aircraft details, predicted non-deviated trajectories, and surrounding traffic conditions. Our approach facilitates large-scale analysis of air traffic control decision-making, providing a foundation for developing conflict resolution models that better reflect operational practices. This paper details the methodology and process used to construct this dataset