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Rotorcraft low-noise trajectories design: black-box optimization using surrogates
No full textInternational audienceThis paper addresses the noise-minimal trajectory optimization problem for a specific type of aircraft: rotorcraft. It relies on a realistic noise footprint computation software provided by industry that is black-box. Locally optimal trajectories are computed through a tailored solution approach based on the Mesh-Adaptive Direct Search algorithm. We propose multiple surrogates defined according to our knowledge of the problem, including a surrogate relying on the physics of the problem (approximating the rotorcraft noise model), and another based on a machine learning (neural network) method. The proposed solution approach is further enhanced by the computation of an appropriate starting guess through a path planning algorithm tailored to the problem, and by the reduction of the variable space domain. The performance of the proposed methodology both in terms of quality of the solutions (trajectories exhibiting significant noise reduction compared to those currently flown in practice) and computing time is illustrated through numerical experiments on realworld case studies
Discrete Turbulent Spectrum Modelling for 2D Split-Step Electromagnetic Propagation Schemes
No full textInternational audienceThe multiple phase screen method is widely used for modelling the electromagnetic propagation in a turbulent medium. In this technique, the turbulent phase screens are classically generated from a continuous Von-Karman Kolmogorov scintillation spectrum. Recent works led to the development of an auto-coherent split-step wavelet propagation method based on a discrete formulation of the parabolic wave equation. In this configuration, the use of continuous spectra is no more suitable. In this paper, we propose an auto-coherent generation method of the turbulent phase screens. To do so, a discrete formulation of the classical Von-Karman Kolmogorov spectrum is introduced. The impact of the modelled turbulence is finally discussed through the computation of the log-amplitude variance to validate this approach
Enhancing Travel Resilience: Integrating Alternative Path-Based Robustness Metric in Route Optimization
No full textUnforeseen disruptions, including accidents, adverse weather conditions, and temporary construction, frequently hinder traffic flow in road transportation, forcing passengers to alter their routes. These incidents impart stress and delays on travelers.This article delves into the optimization of itineraries to minimize the impact of disruptions on passengers' journeys, with a focus on the criteria to be considered.We present a new metric for topological robustness that focuses on alternative paths and can be integrated into passengers' decision-making processes for choosing a route.Our simulations, based on static traffic assignment and varying levels of robustness, demonstrate that these robust paths are an effective way to mitigate travel delays and excessive travel time during disruptions
Development of a Mission-Tailored Tail-Sitter MAV
No full textInternational audienceVertical takeoff and landing (VTOL) vehicles are among the most versatile UAVs, appropriate for various missions. Given that there are still open challenges regarding the VTOL design, this paper presents the full development and test cycle of a tail-sitter. IMAV 2022 competition rules were used to define the mission. A multidisciplinary design and optimization strategy was defined with the goal of maximizing competition score considering design, manufacturing, and competition constraints. The resulting vehicle was designed to fly at 18[Formula: see text]m/s while carrying 200[Formula: see text]g of payload with a total weight of approximately 720[Formula: see text]g. It flew for roughly 13 min at IMAV2022, helping its team to achieve 1st place at the “Package delivery challenge”. Further flight tests revealed the ultimate endurance performance as 18[Formula: see text]min
Development of flight guidance control laws for a web based air traffic control simulator
No full textInternational audienceENAC (École Nationale de l'Aviation Civile), the French civil aviation university, offers a comprehensive training program for aspiring air traffic controllers. The program combines theoretical classroom-based instruction with practical hands-on experience using simulators and real-time scenarios. ENAC's proprietary software, ELSA (ENAC Light Simulator for Atc), plays a crucial role in providing online air traffic control simulation exercises for training purposes. This paper focuses on the implementation of trainee clearances in ELSA, specifically how these clearances are converted into commanded values which feed dedicated guidance control loops for a point-mass aircraft model. The simplicity and realism of the point-mass aircraft model contribute to an effective Air Traffic Control (ATC) training experience
Cost-Effective Offloading Strategies for UAV Contingency Planning in Smart Cities
No full textInternational audienceIn the near future, smart cities are expected to become more prevalent, with Uncrewed Aerial Vehicles (UAVs) playing a key role in making cities more efficient and sustainable. Effective path planning is essential for the safe and efficient integration of drones into urban airspace. However, one potential limitation of UAVs is that they may not have sufficient computing power to perform real-time contingency planning when encountering obstacles. To address this challenge, this work proposes edge-assisted offloading scenarios where contingency planning is considered as a resource-intensive task that can be offloaded to nearby edge nodes. We implemented and compared various strategies for generating offloading plans in a robot swarm simulator based on latency and cost metrics. Our evaluation revealed that the offloading plans generated using the genetic algorithm tended to perform better in terms of average latency or cost per offloading, albeit with higher runtime overhead compared to the other strategies
Algorithme évolutionnaire pour la résolution, en continu, de conflits aériens
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Planification stratégique de trafics drones aériens
No full textLarge numbers of Urban Air Mobility (UAM) vehicles are expected to operate in urban airspace in the near future. However, this growth will soon exceed the capacities of current airspace and air traffic management systems and put strains on transportation infrastructure, resulting in undesirable outcomes such as traffic congestion, complex traffic situations, delays, etc. As a result, innovative UAM solutions are required to ensure safe and efficient urban transportation. In this thesis, we focus on strategic planning in unmanned aircraft system traffic management, including airspace organization and management and traffic flow management. Specifically, we develop approaches for UAM route network design and air traffic assignment. The structure of the UAM route network strongly impacts many aspects of the operating traffic flow. The UAM route network is expected to be well-designed for the desired network operations, especially with dense traffic demands. In order to minimize the impact on existing air traffic management systems, this thesis proposes a comprehensive framework to design a UAM route network in low-altitude urban airspace in the presence of obstacles and hazardous airspace. Using a variety of open-source data, this approach is applied as a case study for parcel delivery services using UAVs as UAM vehicles in Singapore's urban airspace. Firstly, The UAM route network is designed as a grid-based network that avoids obstacles and airspace within which the aircraft is prohibited. Then, the link cost is defined in terms of noise impact on populations, airspace safety, and flight efficiency. Unlike most research that only calculates the shortest path, we formulate a k-shortest path problem with diversity to select feasible routes between origin-destination pairs that minimize the route cost. The feasibility of this approach is demonstrated in the experiment, which can also be easily transferred to other scenarios. The impact of different parameter settings for link costs on UAM services is also explored. The feasible routes with low similarity provide more travel options, which can be used as pre-computed routes for air traffic assignment models. To adapt the increasing demand to the current airspace capacity, we proposed several air traffic assignment models, including two static air traffic assignment models for single-layer and multi-layer two-way UAM route networks and a dynamic air traffic assignment model for multi-layer two-way UAM route networks in order to mitigate the congestion and complexity and organize the structure of air traffic flow. Firstly, at the macroscopic level, UAM operations are modeled as flows by aggregating the individual vehicle dynamics to describe the overall flow features with respect to the dense traffic volume. The flows are structured into UAM route networks, in which the air routes are modeled as corridors or volume segments. Then, the air traffic assignment model is formulated as an optimization problem. The objective functions are modeled to describe the air traffic complexity based on the linear dynamical system and the congestion based on energy consumption and traffic density. The simulation-based framework including different optimization approaches is proposed to efficiently solve these problems. Computational experiments are performed on case studies of UAM route networks at various scales. The comparisons with regard to conventional traffic assignment algorithms are presented. The results show that the proposed approach is capable of assigning flows in an efficient and effective manner, significantly reducing the complexity and congestion of the UAM operations. The proposed model can be used to assist regulators and air navigation service providers for air traffic assignments in the strategic planning of UAM operations.Un grand nombre de véhicules de mobilité aérienne urbaine, en anglais Urban Air Mobility (UAM), devraient opérer dans l'espace aérien urbain dans un avenir proche. Cette croissance dépassera bientôt les capacités de l'espace aérien et des systèmes de gestion du trafic aérien actuels et mettra à rude épreuve les infrastructures de transport, entraînant des résultats indésirables tels que des encombrements, des situations de trafic complexes, des retards, etc. Par conséquent, des solutions UAM innovantes sont nécessaires pour garantir un transport urbain sûr et efficace. Dans cette thèse, nous nous concentrons sur la planification stratégique du trafic des drones, y compris l'organisation ainsi que la gestion de l'espace aérien et des flux de trafic. Plus précisément, nous développons des approches pour la conception du réseau de routes UAM et l'affectation du trafic aérien associé. Afin de minimiser l'impact sur les systèmes de gestion du trafic aérien existants, cette thèse propose une méthodologie pour concevoir un réseau de routes UAM dans l'espace aérien urbain à basse altitude en présence d'obstacles et d'espaces aériens dangereux. Sur la base de diverses données publiques, cette approche a été appliquée à l'espace aérien urbain de Singapour comme cas d'étude pour les services de livraison de colis utilisant des UAVs. Dans un premier temps, le réseau de routes UAM est conçu à partir de grilles qui évitent les obstacles et les zones interdites. Ensuite, les coûts d'arcs sont définis en termes d'impact sonore sur les populations, de sécurité de l'espace aérien et d'efficacité du vol. Nous formulons un problème de k-plus courts chemins avec diversité pour sélectionner les routes réalisables qui minimisent le coût associé. Les itinéraires réalisables avec une faible similarité fourniront plus d'options de trajet, qui peuvent être utilisées pour générer le réseau de routes UAM afin de prendre en charge les opérations à haute densité et à flux complexe. En outre, l'impact de différents paramètres pour les coûts d'arcs sur les services UAM est également analysé. Bien que la méthodologie proposée soit appliquée à l'espace aérien urbain de Singapour, elle pourrait facilement être généralisée à d'autres espaces aériens urbains dans le monde. Pour adapter la demande croissante à la capacité actuelle de l'espace aérien, nous avons proposé plusieurs modèles d'affectation du trafic aérien, notamment deux modèles statiques pour les réseaux de routes UAM à une et à plusieurs couches et un modèle dynamique pour les réseaux de routes UAM birectionnels multicouches, afin d'atténuer la congestion et la complexité et d'organiser la structure du flux de trafic aérien. Premièrement, au niveau macroscopique, les opérations UAM sont modélisées sous forme de flux de trafic en agrégeant la dynamique des véhicules individuels. Les flux sont répartis sur des réseaux de routes UAM, pour lesquels les routes aériennes sont modélisées comme des couloirs ou des segments volumétriques. Ensuite, le modèle d'affectation du trafic aérien est formulé comme un problème d'optimisation. Les critères sont modélisées de manière à décrire la complexité et la congestion du trafic aérien sur la base d'un système dynamique linéaire. Un cadre basé sur la simulation, comprenant différentes approches d'optimisation, est proposé pour résoudre efficacement ces problèmes. Des expériences informatiques sont réalisées sur des études de cas de réseaux de routes UAM à différentes échelles. Une comparaison avec les algorithmes conventionnels d'affectation du trafic est présentée. Les résultats montrent que l'approche proposée est capable d'affecter les flux de manière efficace et efficiente, en réduisant de manière significative la complexité du réseau de routes UAM 3D. Le modèle proposé peut être utilisé pour aider les régulateurs et les fournisseurs de service de navigation aérienne pour l'affectation du trafic aérien dans la planification stratégique des opérations UAM
Merging Control and Feedback to Reduce Mode Confusion in the Cockpit
No full textInternational audienceMode confusion and automation surprises in aviation raise questions about the design of flight deck interfaces. Prior research investigated the use of the current interfaces and how they can impact the pilot’s awareness of modes, and proposed design solutions to reduce mode confusions by improving feedback and interaction with modes. This paper explores a novel design that brings together mode control and feedback in a single interface. The interface aims to reduce mode confusions. Moreover,the paper highlights 5 key dimensions that influenced the design. In the future, we intend to evaluate the proposed interface to validate its benefits
Prosumers: Grid Storage vs Small Fuel-Cell
No full textThe number of prosumers-consumers equipped with decentralized production-is expected to increase following the revised Renewable Energy Directive (2018/2001) and the rising energy prices. The economic literature suggests there is room for demand-side storage that can take two forms: decentralized or centralized. The schemes promoting investments in solar capacity physically allow for only one type of demand-side storage. One may wonder about the conditions under which consumers invest in different technologies. We build a stylized microeconomic model of the energy market and perform a numerical evaluation, using publicly available data from France, to compare two regulations-price and quantity-from our representative consumer's and the Distributed System Operator's points of view. The two energy regulations lead to three types of profiles: consumers, prosumers, and storers. These profiles are in line with previous studies focusing on price regulation. With quantity regulation, a grid tariff such that consumers invest in storage depends on endogenous parameters. The results suggest that with the current price regulation in France, only a smaller feed-in-tariff would encourage investments in decentralized hydrogen-based storage. A grid tariff such that consumers inject energy into the grid would not reflect the cost of centralized hydrogen-based storage. However, a quantity regulation would be less costly to support