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Testing for Elderly Fragility: A Valuable Public Policy and an Opportunity for Postal Operators
No full textInternational audienc
Impact of a civil aviation GNSS receiver temporal blanker in presence of RFI DME/TACAN signals
No full textInternational audienceIn the L5/E5a band, the predominant Radio Frequency Interferences (RFI) impacting GNSS are the DME/ TACAN pulsed signals. To mitigate its impact, airborne DFMC GNSS receivers must implement a Temporal Blanker (TB), a device setting to zero the I/Q received signal samples having an instantaneous power envelope above a certain threshold. The RFI and TB presence decrease the effective Carrier-to-Noise ratio, C/N0,eff, which determination is critical to guarantee GNSS-based Safe-of-Life service in civil aviation. To accurately determine C/N0,eff, the exact model of the normalized Power Spectrum Density (PSD) of each RFI signal at the TB output, or post-blanker RFI signal, is required. However, the post-blanker RFI signal PSD is difficult to calculate since a TB is a strongly non-linear device and its behavior is aircraft location and flight altitude (L&A) dependent. To address this problematic, in this work a new model of a post-blanker DME/TACAN signal is proposed from the multiplication of the before-blanker RFI signal by two artificial signals; autoblanking, triggering of the blanker by the DME/TACAN signal itself, and blanking-by-others, triggering of the blanker by other DME/TACAN beacons signal. The proposed model allows the mathematical determination of a mean post-blanker DME/TACAN signal PSD and is L&A customized. In comparison, previous reference or proposed PSD models were either not-mathematically justified approximations or did not consider the TB effect (simplification); and neither were L&A customized. The proposed post-blanker DME/TACAN signal PSD expression is verified through simulations with differences smaller than 0.11dB. Comparisons with reference and simplified models are conducted in terms of PSD, Spectral Separation Coefficient (SSC) and RI (linked to C/N0,eff. Previous reference model shows to be a loose approximation, and simplified models present less accurate PSD and SSC results but a small RI underestimation. Finally, the RFFE block impact,..
Method for selecting a portion of an encephalographic signal, devices and corresponding program
No full textA method for selecting data derived from an electroencephalogram, in the form of a set of starting scalograms, each scalogram being calculated from a portion of an electroencephalographic signal. The method includes: extracting, via an artificial neural network, a set of candidate scalograms; and for some candidate scalograms of the set of candidate scalograms: calculating characteristics of the electroencephalographic signal portion corresponding to the candidate scalogram; and when the plurality of characteristics are within prerequisite value ranges, selecting the electroencephalographic signal portion of the candidate scalogram within an electroencephalographic signal selection data structure
Emergency Trajectory Structure for UAVs
No full textInternational audienceThe study of the design of emergency trajectories of air vehicles is one of the key elements in improving airspace safety for air vehicles. The aim is to lighten pilots' workload, offering quick and effective solutions. However, almost all flight optimizers proposed in the literature still need to be completed when it comes to resolving emergency contexts, which presents a significant disadvantage to the advancement of scientific research. This resolution is based on the following problems: (a) finding paths free of obstacles, (b) ensuring their flight capacity, and finally, (c) calculating trajectories optimizing several criteria with a calculation time constraint (a few minutes). This document analyzes the safety landing problem and proposes an architecture that effectively reduces complexity and ensures solvability within a reasonable computational time. This architectural framework is designed to be adaptable, allowing for testing several algorithms to provide a quick overview of their strengths and weaknesses in this context. The primary aim of these tests is to benchmark the computational time of the overall architecture, ensuring that this adaptable framework is fully capable of handling the problem's complexity. It is important to note that the algorithms chosen address only a simplified version of the problem. The initial results are promising in terms of time response and the potential to enhance the representativeness and complexity of the problem. The next phase of our research will focus on striking the right balance between complexity, representativity, and computational time, aiming to impact emergency response significantly.</div
Impact of the COVID-19 pandemic on bike-sharing uses in two French towns: the cases of Lyon and Toulouse
No full textInternational audienceUrban areas have been dramatically impacted by the sudden and fast spread of the COVID-19 pandemic.As one of the most noticeable consequences of the pandemic, people have quickly reconsidered their travel options to minimize infection risk. Many studies on the Bike Sharing System (BSS) of several towns have shown that, in this context, cycling appears as a resilient, safe, and very reliable mobility option. Differences and similarities exist about how people reacted depending on the place being considered, and it is paramount to identify and understand such reactions in the aftermath of an event in order to successfully foster permanent changes. In this paper, we carry out two analyses, both from a geographical and temporal point of view: on the one hand, we compare the short-term effects of the pandemic on BSS usage in two French towns (Toulouse and Lyon), and on the other, hand we analyze its mid-term effects in Toulouse. We used Origin/Destination data for four years: 2019 (pre-pandemic), 2020 (pandemic before massive vaccination campaigns), 2021 (pandemic after massive vaccination campaigns), and 2022 (year after the pandemic peak). We consider two complementary quantitative approaches. Our results confirm that cycling increased during the pandemic, more significantly in Lyon than in Toulouse, with rush times remaining exactly the same for the four years, even during the lockdowns. The year 2021 shows a transitional profile between 2020 and 2022 that could be attributed to adaptation to living with COVID and perhaps also to the increased sense of safety brought by the vaccination campaign. We also found that trip duration during the pandemic situation was longer both on working days and weekends. Comparing BSS traffic with road traffic and public-transport validations shows that cycling is a resilient mode of transport in a pandemic. Among several general observations, we note that peripheral/city center BSS flow is more noticeable in Toulouse than in Lyon and that student BSS usage is more specific in Lyon
Potential Flow Theory Based Guidance Algorithm for 3D Obstacle Avoidance in Cluttered Urban Environments
No full textInternational audienceIn this paper, an existing guidance method based on potential flow theory is enhanced through the incorporation of 3D models of obstacles, thereby allowing for the optimal utilization of available airspace in urban air mobility applications. The proposed 3D guidance method addresses the limitations of the previous 2D approach, enabling navigation around complex obstacles such as tunnels and torus-like structures. The effectiveness of the proposed algorithm is demonstrated through scaled hardware experiments conducted at The Toulouse Occitanie Drone Flight Area in France. The experimental results demonstrate the successful real-time guidance and collision avoidance capabilities of the proposed algorithm in cluttered environments for multiple aerial vehicles, with an effective utilization of vertical and horizontal space. This improvement makes the proposed 3D guidance algorithm a suitable candidate for urban air mobility operations
Impact des répéteurs GNSS sur les récépteurs de l'aviation civile
No full textInternational audienceWith the escalating prevalence of radio-frequency 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 rebroadcastthem to GNSS receivers in sight) contributes to this threat landscape, by compromising the operating performance of thenearby GNSS receivers. This work investigates the impact of onboard meaconers on aircraft GNSS receivers, emphasizing theirdetrimental effects on the accuracy, availability, and integrity of the GNSS estimated positions. Through mathematical modelingand highly realistic simulations, the influence of meaconing on the GNSS observables (code, phase, smoothed pseudoranges,carrier-to-noise density ratio C/N0 estimations), and on the main processing blocks of a standardized aircraft GNSS receiver(C/N0 threshold, measurement quality monitoring, step detector, fault detection procedure and protection level checks) hasbeen deeply characterized. The findings indicate that onboard meaconers can induce substantial degradations in the GNSSsignal tracking, resulting in significant positioning errors and availability drops that compromise both the flight operations andsafety. For specific meaconer characteristics, the meaconer could completely jeopardize the aircraft’s receiver ability to computea position, induce position errors up to 40 meters, or provoke continuous misleading position information and integrity hazards.The study highlights the importance for aviation bodies to consider the onboard meaconing threats. Additionally, the findingspresent valuable guidance for pilots and manufacturers in identifying and interpreting onboard meaconing interference, therebystrengthening the reliability of GNSS-based navigation systems in the aviation sector
Caractérisation de la situation de multitrajets d'un répéteur GNSS
No full textInternational audienceWith the escalating prevalence of in-band interference, the vulnerability of Global Navigation Satellite System (GNSS) receiversto potential jamming or spoofing threats has become a critical concern. The proliferation of GNSS repeaters, commonly knownas meaconers (electronic devices that intercept GNSS signals, amplify them, and subsequently rebroadcast them) contributesto this threat landscape, by compromising GNSS accuracy, availability, continuity, and integrity of the nearby receivers. Thispaper investigates the impact of a meaconer on a GNSS receiver, when the received satellite signals are in the multipath situation(from the classification of Hussong et al. (2023)). The multipath situation is the situation when the meaconing useful GNSSsignal affects the tracking of the authentic GNSS signal, as if it were exposed to a classical multipath. This paper characterizesand bounds the estimated carrier-to-noise ratio (C/N0) and tracking loop outputs in the multipath situation. Then, this paperidentifies the geometrical conditions under which a satellite is affected by meaconing multipath. Finally, extensive simulationsvalidate the mathematical models by comparing the expected C/N0 and tracking loop outputs to highly realistic simulationresults. The findings reveal significant distortions in the C/N0 for satellites in the multipath situation. In rapid-dynamicscenarios, the C/N0 can decrease up to 20 dB.Hz, and C/N0 distortions may have more complex yet predictable patterns inslow-dynamic scenarios. The delay lock loop (DLL) outputs are shown to be corrupted by deterministic offsets up to ±15 meters,accompanied by increased standard deviations due to the degraded tracking performance caused by the meaconer interference
Making Moral Decisions With Artificial Agents As Advisors. An fNIRS Study
No full textInternational audienceArtificial Intelligence (AI) is on the verge of impacting every domain of our lives. It is increasingly being used as an advisor to assist in making decisions. The present study aimed at investigating the influence of moral arguments provided by AI-advisors (i.e., decision aid tool) on human moral decision-making and the associated neural correlates. Participants were presented with sacrificial moral dilemmas and had to make moral decisions either by themselves (i.e., baseline run) or with AI-advisors that provided utilitarian or deontological arguments (i.e., AI-advised run), while their brain activity was measured using an fNIRS device.Overall, AI-advisors significantly influenced participants. Longer response times and a decrease in right dorsolateral prefrontal cortex activity were observed in response to deontological arguments than to utilitarian arguments. Being provided with deontological arguments by machines appears to have led to a decreased appraisal of the affective response to the dilemmas. This resulted in a reduced level of utilitarianism, supposedly in an attempt to avoid behaving in a less cold-blooded way than machines and preserve their (self-)image. Taken together, these results suggest that motivational power can led to a voluntary up-and downregulation of affective processes along moral decision-making.</div
