Archive ouverte de l'ENAC
Not a member yet
3458 research outputs found
Sort by
Supporting drone mission planning and risk assessment with interactive representations of operational parameters
No full textInternational audienceDrone missions in urban areas or at long range offer new opportunities for drone operators but require approval from the authorities due to the potential risks. Obtaining authorization is complex and time-consuming since operators must produce and often iterate on a concept of operation and risk analysis documents to accommodate the authorities’ expectations. Our goal is to support the drone mission planning process to make it more efficient so that more and safer operations can be designed and authorized. In this paper, we describe our work designing and assessing interactive representations of operational parameters on maps to enhance thinking and accelerate the process from early concept definition to mission execution. We first collaborated with an operator during a longitudinal study that enabled us to refine and explore our concepts and prototype with real-world use cases. We then collected the feedback from authorities to evaluate the ability of our prototype to match the needs and requirements beyond our first study. Our results indicate that visually representing the concept of operations makes its description more accurate and easier to understand. We also found that exploring the impact of the operational parameters on safety actively supports risk identification and the formulation of adequate mitigation. We believe that our work can inspire the design of future safety support systems and may also contribute to supporting the collaborative process between operators and authorities needed for drone operations in the Specific category
Surrogate model development for optimized blended-wing-body aerodynamics
No full textInternational audienceIn the conceptual design phase of conventional-configuration aircraft, calibrated low-fidelity methods provide sufficiently accurate estimates of aerodynamic coefficients. It has been observed, however, that for blended-wing-body aircraft, important flow effects are not captured adequately with low-fidelity aerodynamic tools. Consequently, high-fidelity methods become necessary to study blended-wing-body aerodynamics. Since repeated function calls are needed in an optimization loop, high-fidelity analysis is prohibitively expensive in the conceptual design phase, where several optimization scenarios are considered. In this paper, the integration of high-fidelity data for blended-wing-body aircraft for a mission calculation module is presented. A surrogate model based on Gaussian processes (GPs) with acceptably low prediction error is sought as an alternative to RANS CFD. Three adaptations are considered: sparse GPs, mixtures of GP approximators, and need-based filtering for GP. The results provide benchmark values for this case and show that the combination of subsonic and transonic behaviors in the training set is problematic and that, for the considered datasets, sparse GP models suffer from oversmoothing while mixtures of GPs models suffer from overfitting. From the error levels, it is observed that a GP with an infinitely-differentiable squared exponential kernel based on reduced data pertinent to mission analysis is the most effective option
A meta-analysis on air traffic controllers selection: cognitive and non-cognitive predictors
No full textInternational audienceThis psychometric meta-analysis investigated the relation of cognitive and non-cognitive factors to the training success of Air Traffic Controllers by synthesizing 51 studies (N = 65,839). Cognitive factors were classified by Cattel-Horn-Carrol theory. Cognitive composite scores and work samples were also included. Non-cognitive factors consisted of Big Five personality traits, biodata, motivation and non-cognitive composite scores. Medium effect was measured for cognitive factors (k = 45, p = .37). Quantitative knowledge, processing speed, work sample, short-term working memory, cognitive composite and visuo-spatial processing predictors showed large effects (p > .30). Significant moderating effects of criterion nature and period of publication were observed. Initial training (k = 30, p = .50) was generally better predicted than on-the-job training (k = 25, p = .18). Better predictive validity was measured from the 60's to nowadays. For non-cognitive factors, only a small effect was measured (k = 24, p = .15). Non-cognitive composites and education showed large effects (p > .30). No significant relation was measured between Big Five personality traits and success criteria. The present findings suggest that selection processes used for Air Traffic Controllers should focus on cognitive predictors or other methods of assessments. Data and scripts can be found at https://osf.io/mkyw7/
An Automated Emergency Airport and Off-Airport Landing Site Selector
No full textInternational audienceWe present a novel landing site selector capable of selecting suitable landing sites (airport and off-airport) for emergency landings. In a first step, information from several databases which includes, for instance, elevation data, is gathered by our system. Then, this information is processed in order to create a list of potential landing sites ranked according to several factors, such as the characteristics of the runway, the type of emergency or the current weather. A generic scenario and case studies have been defined in order to test the landing site selector, ultimately leading to a series of trajectories-generated with an emergency trajectory generator presented in previous publications-safely leading the aircraft to one of the landing sites chosen by our system
RFC 9265 Forward Erasure Correction (FEC) Coding and Congestion Control in Transport
No full textInternet Research Task Force (IRTF) - Request for Comments: 9265 - Category: Informational - ISSN: 2070-1721Forward Erasure Correction (FEC) is a reliability mechanism that is distinct and separate from the retransmission logic in reliable transfer protocols such as TCP. FEC coding can help deal with losses at the end of transfers or with networks having non-congestion losses. However, FEC coding mechanisms should not hide congestion signals. This memo offers a discussion of how FEC coding and congestion control can coexist. Another objective is to encourage the research community to also consider congestion control aspects when proposing and comparing FEC coding solutions in communication systems. This document is the product of the Coding for Efficient Network Communications Research Group (NWCRG). The scope of the document is end-to-end communications; FEC coding for tunnels is out of the scope of the document
Méthode split-step wavelet pour la propagation troposphérique en 3D
No full textInternational audiencePour des systèmes électromagnétiques, comme le radar, il est important de modéliser précisément la propagation sur de longues distances en tenant compte des effets de l'environnement. Une méthode répandue dans ce contexte est basée sur la résolution de l'équation parabolique par split-step Fourier (SSF). Cependant, pour des scénarios 3D elle est limitée par son temps de calcul et sa taille mémoire. Récemment, une méthode efficace en temps et mémoire en ondelettes a été proposée en 2D. Dans cet article, nous généralisons la méthode à des scénarios 3D. Nous montrons également qu'elle est de complexité plus faible que SSF. Des tests numériques sont également proposés pour montrer les avantages de la méthode en comparaison de SSF
Sector Entry Flow Prediction Based on Graph Convolutional Networks
No full textInternational audienceImproving short-term air traffic flow prediction can help forecast demand and maximize existing capacity by tactical air traffic flow management. Most existing studies in flow prediction lacks consideration of the dynamic, structural, and interrelated nature of air traffic flows in the airspace. Therefore, this paper proposes to predict sector entry flows based on graph convolutional networks, which consider the dynamic spatial-temporal features of air traffic from a graph perspective. First, we specify a sector entry flow based on its upstream and downstream sectors. Then, each entry flow is denoted as a node in a graph. The weighted edges between the nodes are learned from a Word2vec model based on air traffic flows among the nodes. With the weighted graph constructed and the temporal flows on the nodes extracted from the flight trajectories, an Attention-based Spatial-Temporal Graph Convolutional Network (ASTGCN) module is adopted to capture spatial-temporal features of recent, daily-periodic, and weekly-periodic flows in the graph. Finally, The outputs from the ASTGCN module based on the three features are fused to generate the final prediction results. The proposed method is applied on 164 sectors of French airspace for one-month ADS-B data)from Dec 1, 2019, to Dec 31, 2019) which includes 158,856 flights. Results show that, the proposed method outperforms the well established Long shortterm memory (LSTM) model, and demonstrates better capability in predicting rapid changes in traffic flow and has relatively smaller decrease in prediction accuracy as the prediction timewindow increases
Towards a Novel UAV Position Tracking and Reporting System for Very Low Level Airspace
No full textInternational audienceThe integration of Unmanned Aircraft Systems into the airspace is a challenging, complex task for both operators and regulators. To ensure a safe and secure UAS integration, they should rely on wide variety of dependable subsystems , including a tracking and position reporting system. This paper proposes a system architecture for tracking and position reporting of UAS in very-low level airspace. The system leverages low-latency communications and distributed computing to offer highly available, consistent tracking information. Preliminary results suggest that our approach is especially useful for the traffic management and operations in densely populated areas
CandyFly: Bringing fun to drone pilots with disabilities through adapted and adaptable interactions
No full textInternational audienceFlying drones is an increasingly popular activity. However, it is challenging due to the required perceptual and motor skills for following and stabilizing the drone, especially for people with special needs. This paper describes CandyFly, an application supporting people with diverse sensory, cognitive and motor impairments to pilot drones. We observed an existing accessible piloting workshop and evaluated CandyFly during eight additional workshops over three and a half years using a research-through-design process and ability-based design methods.We identified users' needs, formulated requirements and explored adaptive interactions such as using pressure-sensitive keys, adjusting controls to the pilots’ range of motion, or limiting the drone’s degrees of freedom to cope with a broad range of disabilities.Our results show that the pilots and their caregivers enjoyed flying and emphasized CandyFly’s ability to be tailored to specific needs. Our findings offer a framework for designing adaptable systems and can support the design of future assistive and recreational systems
Price Competition and Endogenous Product Choice in Networks: Evidence from the US Airline Industry
No full textInternational audienceWe develop a two-stage game in which competing airlines first choose the networks of markets to serve in the first stage before competing in price in the second stage. Spillovers in entry decisions across markets are allowed, which accrue on the demand, marginal cost, and fixed cost sides. We show that the second-stage parameters are point identified, and we design a tractable procedure to set identify the first-stage parameters and to conduct inference. Further, we estimate the model using data from the domestic US airline market and find significant spillovers in entry. In a counterfactual exercise, we evaluate the 2013 merger between American Airlines and US Airways. Our results highlight that spillovers in entry and post-merger network readjustments play an important role in shaping post-merger outcomes