Multimodal transportation represents an innovative approach to contemporary mobility challenges in logistics and transportation. By skillfully integrating different modes of transportation, multimodal transportation provides a comprehensive and efficient solution to the need to move goods and people. The synergistic combination of different modes of transportation creates complex, interdependent multimodal networks, where the failure of a single element can have a significant impact on the entire network. This thesis focuses on the analysis of the vulnerability of transportation systems to disruptions, and proposes a topological approach aimed at guaranteeing the minimum...

Simulation-based problems involving mixed-variable inputs frequently feature domains that are hierarchical, conditional, heterogeneous, or tree-structured. These characteristics pose challenges for data representation, modeling, and optimization. This paper reviews extensive literature on these structured input spaces and proposes a unified framework that generalizes existing approaches. In this framework, input variables may be continuous, integer, or categorical. A variable is described as meta if its value governs the presence of other decreed variables, enabling the modeling of conditional and hierarchical structures. We further introduce the concept of partially...

This paper focuses on Geodesic Principal Component Analysis (GPCA) on a collection of probability distributions using the Otto-Wasserstein geometry. The goal is to identify geodesic curves in the space of probability measures that best capture the modes of variation of the underlying dataset. We first address the case of a collection of Gaussian distributions, and show how to lift the computations in the space of invertible linear maps. For the more general setting of absolutely continuous probability measures, we leverage a novel approach to parameterizing geodesics in Wasserstein space with neural networks. Finally, we compare to classical tangent PCA through various...

Over the last few decades, multicopters have become significantly popular because of their various applications. However, multicopters suffer from poor endurance performance as compared to other aircraft configurations with lifting surfaces. In this paper, a co-design approach for the multicopter structure and propulsive system is presented with the objective of improving the energetic efficiency of the vehicle, while respecting dynamic performance requirements. For this purpose, the approach uses a bi-level formulation to optimize concurrently the design and the control. The methodology offers the possibility to activate or not a passive fault tolerant strategy in the...

En communications optiques spatiales satellite-sol, une problématique majeure est la traversée atmosphérique. La détection cohérente est aujourd’hui une solution privilégiée par rapport à la détection directe, car elle permet l’utilisation de modulations en phase et donc une meilleure efficacité énergétique et spectrale. Le projet CALICO (Compensation des pertes Atmosphériques de LIen laser satellite-sol en détection COhérente) a pour objectif de concevoir un récepteur cohérent capable d’assurer la démodulation homodyne d’un signal QPSK en présence d’un effet Doppler important. Le traitement réalisé doit alléger le besoin en contrôle ou correction d’erreur, et ainsi...

A variety of science orbit configurations have been proposed for a future Enceladus-orbiting mission. Inserting a spacecraft into these orbits requires performing one or more maneuvers to transfer from the endgame conditions of the Saturn-centric moon-tour to the desired configuration. In this work, we propose two different methods for computing these transfers. In the first method, by taking into account the multibody dynamics of the system, the spacecraft can be inserted onto a stable manifold of an unstable staging orbit, and then transfer from this staging orbit to the science orbit. In the second method, a single insertion maneuver is performed at either the apoapse...

DVSim : un simulateur de vision événementielle pour l'apprentissage de réseaux de neurones à impulsions

DVSim : un simulateur de vision événementielle pour l'apprentissage de réseaux de neurones à impulsions

<div><p>We present an adaptive control scheme to enable the emergence of order within distributed, autonomous multi-agent systems. Past studies showed that under high-density conditions, order generated from traffic-following behavior reduces travel times, while under low densities, choosing direct paths is more beneficial. In this paper, we leveraged those findings to allow aircraft to independently and dynamically adjust their degree of traffic-following behavior based on the current state of the airspace. This enables aircraft to follow other traffic only when beneficial. Quantitative analyses revealed that dynamic trafficfollowing behavior results in lower aircraft...