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Modélisation formelle de systèmes de drones civils à l'aide de méthodes probabilistes paramétrées

Abstract : Unmanned Aerial Vehicles (UAV) are now widespread in our society and are often used in a context where they can put people at risk. Studying their reliability, in particular in the context of flight above a crowd, thus becomes a necessity. In this thesis, we study the modeling and analysis of UAV in the context of their flight plan. To this purpose, we build several parametrics probabilistic models of the UAV and use them, as well as a given flight plan, in order to model its trajectory. Our most advanced model takes into account the precision of position estimation by embeddedsensors, as well as wind force and direction. The model is analyzed in order to measure the probability that the drone enters an unsafe zone. Because of the nature and complexity of the obtained models, their exact verification using classical tools such as PRISM or PARAM is impossible. We therefore develop a new approximation method, called Parametric Statistical Model Checking. This method has been implemented in a prototype tool, which we tested on this complex case study. Finally, we use the result to propose some ways to improve the safety of the public in our context.
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Submitted on : Monday, July 6, 2020 - 12:09:52 PM
Last modification on : Wednesday, October 13, 2021 - 3:52:02 PM
Long-term archiving on: : Friday, September 25, 2020 - 1:48:58 PM


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  • HAL Id : tel-02890410, version 1


Ran Bao. Modélisation formelle de systèmes de drones civils à l'aide de méthodes probabilistes paramétrées. Génie logiciel [cs.SE]. Université de Nantes, 2020. Français. ⟨tel-02890410⟩



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