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Theses

Modélisation et surveillance de systèmes Homme-Machine : application à la conduite ferroviaire

Abstract : The scope of the thesis is the monitoring of human-machine systems, where the operator is the driver of rail-based transportation system. Our objective is to improve the security of the system preventing and avoiding factors that increase the risk of a human error. Two major problems are identified: characterization, or how to determine indicative and discernible phases of driver's activity and representation, or how to describe and codify driver's actions and its repercussions on the rail system in a mathematical formalism that will allow unequivocal analysis. In order to bring a solution to those problems, we propose, first-of-all, a behavioral model of the human operator representing his control behavior in continuous-time. To consider inter- and intra-individual differences of human operators and situation changes, we propose a transformation of the latter behavioral model in a new space of representation. This transformation is based on the theory of Hidden Markov Models, and on an adaptation of a special pattern recognition technique. Then, we propose a discrete-time behavioral modeling of the human operator, which represents his actions and takes account of errors and unexpected events in work environment. This model is inspired by cognitive models of human operators. These two aspects allow us to interpret observables with respect to reference situations in order to characterize the overall human operator state. Different information sources are considered; as a result the data are heterogeneous and subject to measuring uncertainties, needing a robust data fusion approach that is performed using a Bayesian Network. Finally, the proposed modeling and fusion methodologies are used to design a reliable and unintrusive vigilance system. This system can interpret driving behaviors and to detect driver’s risky states in order to prevent drowsiness. The theoretical study was tested in simulation to check the validity. Then, a feasibility study was conducted using data obtained during experiments on the LAMIH laboratory railroad platform “COR&GEST”. These results allowed us to plan and implement experiments to be conducted on the future multimodal driving simulator “PSCHITT-PMR”.
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https://hal-uphf.archives-ouvertes.fr/tel-03358680
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Submitted on : Wednesday, September 29, 2021 - 3:10:48 PM
Last modification on : Tuesday, October 19, 2021 - 6:38:14 PM

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  • HAL Id : tel-03358680, version 1

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Nedjemi Rachedi. Modélisation et surveillance de systèmes Homme-Machine : application à la conduite ferroviaire. Automatique / Robotique. Université de Valenciennes et du Hainaut-Cambrésis, 2015. Français. ⟨NNT : 2015VALE0009⟩. ⟨tel-03358680⟩

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