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A new method to compute more appropriate off-block times and taxiing paths for airport surface management
No full textInternational audienceAirports, as critical hubs connecting air and ground transportation, play a key role in managing airspace and ground resources. However, increasing flight volumes and dynamic ground conflicts present significant challenges to accurately predicting taxi times and push-back schedules. These uncertainties make it difficult for existing routing methods to coordinate taxiway usage with runway scheduling. To address this issue, this paper introduces a Reverse Time-Window-based Multiobjective A* algorithm (R-TMOA*), which optimizes taxi routes by routing backward from the runway to the stand. This approach enhances taxi time predictions and improves alignment with DMAN schedules. Through simulations based on recorded operational data from Tianjin Binhai International Airport, R-TMOA* is compared with existing methods, including a basic fixed paths strategy and the classical TMOA* algorithm. Results show that R-TMOA enables 99% of departures to reach the runway on time, supporting punctual pushback and takeoff operations. It reduces conflicts during taxi by 60% and decreases total taxi time by 4,000 seconds per day, while maintaining computational speed efficiency. The proposed reverse routing method further enhances departure scheduling, optimizes taxiway usage, and improves overall airport operational efficiency.</div
Open-Source Framework for Sizing Hybrid and Electric General Aviation Aircraft
No full textInternational audienceThis paper presents FAST-OAD-CS23-HE, an open-source framework that has been developed as an extension of the existing FAST-OAD-GA framework to allow for medium fidelity sizing of hybrid and electric aircraft using component models dependent on operating conditions and sizing criteria. It inherits Overall Aircraft Design methodologies from the original framework and adds a library of models to represent physical components for hybrid powertrains. It also adds a generic methodology that enables the extension to multiphysic simulation for the powertrain and the consideration of synergistic interactions and supports the addition of new components. A graph-based description of the powertrain was chosen to easily describe complex powertrains that could be considered in innovative architectures as well as ease the future interfacing with external tools. In addition to that, the graph-based approach allows the automation of the construction of the design problem, which removes the need for users to handle complex scripts. It has been developed after a comparison of existing methodologies and open-source framework in an effort to bridge the gap in terms of preliminary design of electric aircraft. With the models implemented with the default delivery of the code, two aircraft were studied to serve as a reference to showcase the capabilities of this framework.<br /
The Presenter in the Browser: Design and Evaluation of Human Interactive Overlays with Web Content
No full textInternational audienceThis research explores the design and evaluation of a webcam-based presentation tool that enables presenters to directly interact with web content via free-hand gestures. Our approach consists of overlaying the webcam video feed on top of web browser content to enable live presentations of any webpage. To support interactive presentations, we designed free-hand gesture interactions with the webpage to enable pointing, clicking, panning, and zooming interactions. We propose three alternatives to enable free-hand clicking: dwell time, modal key control, and a pinching interaction technique. We conducted an exploratory user study of these alternative designs to gather insights on the usability of such systems from a presenter point of view, with a focus on understanding the impact of the three techniques on flow interruptions. The results indicate that the system we propose can be used to deliver presentations effectively and that natural gestures do not disturb the flow of the presentation.</div
Towards transferable models of cyclist route choice : a mode-constrained mixture approach
No full textCities increasingly rely on bike-sharing systems to promote sustainable mobility. These systems generate massive but low-granularity data. Unlike GPS datasets, trip records typically provide only the origin, destination and total duration, making it difficult to infer route structure or behavioral heterogeneity. Despite this limited granularity, some studies have shown that trip-duration distributions are usually well represented by a mixture of log-normal distributions, with a strong linear relationship between the first component mode and the theoretical fastest duration provided by OpenStreetMap. To exploit this relationship, we propose a mode-constrained mixture model, in which the mode of the first component is linearly linked to the theoretical travel time. This approach is validated on the 2.4 million trips recorded in Helsinki–Espoo in 2024, which has the particularity of including both durations and distances. On these data, the lesser variability of distances makes it much easier to identify the groups of the mixture model. The estimated group proportions are then confronted to those estimated from the durations as a way to validate the method. This transferable method offers urban planners a reliable tool to infer route choice without GPS data, supporting the design of cycling infrastructure and the modeling of travel demand
Enabling Incremental SysML Model Verification: Managing Variability and Complexity Through Tagging and Model Reduction
No full textInternational audienceDesigning complex software systems with model-based approaches encounters the recognized state space explosion problem. Typically, only a subset of models can be formally verified, forcing reliance on simulation or testing to verify the entire system. Furthermore, most formal verification tools require a complete reevaluation of properties after even minor modifications to a model. Although incremental formal verification, particularly the incremental model-checking approach of TTool, has been proposed, it still requires modelers to manually select sub-models not facing state space explosion. Unfortunately, this manual model selection is susceptible to errors. This paper presents a twofold contribution to SysML models of software product lines. First, we introduce a SysML model tagging feature that enables designers to explicitly differentiate between various subsystems, such as core and optional features. Second, we develop and implement a model reduction algorithm using dependency graphs (DGs). This algorithm automatically deactivate model elements linked to specific tags, removing both the specified elements and all their logical dependencies provided the DG is acyclic. These two contributions are evaluated for their effectiveness in generating model variants. Together, they facilitate the creation of a core model and an associated set of models, each extended by additional model elements, and make it possible to rely on incremental model-checking. We have implemented the contributions in TTool and applied it to an integrated modular avionics system. This application enables to compare-both manual and automated-model reduction strategies and assess their benefits for TTool users. a</div
Mixed integer quadratically constrained quadratic programming for neural network Lipschitz constant computation
No full textInternational audienceTo ensure or certify the robustness of a neural network, its Lipschitz constant plays a prominent role. However, its calculation is NP-hard and one can only expect to bound or estimate it when computing time is limited. By taking into account activation regions at each ReLU neural network layer as new constraints, we propose new quadratically constrained Mixed Integer Programming (MIP) formulations for the neural network Lipschitz constant computation problem. The solutions of these problems provide lower bounds and upper bounds and we show that these bounds coincide with the Lipschitz constant almost everywhere in the parameter space of the neural network. Using various benchmark architectures and datasets from the literature, we run numerical comparisons of the proposed approach with a polynomial optimization technique, a mixed integer programming technique and a branch and bound method. The results show that, when the computing time budget is limited, the quadratically constrained MIP formulation achieves tighter bounds than the other methods for the L2 and L∞-norms
Optimization of Standard Instrument Departure Routes Using Mixed Integer Linear Programming
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