Modeling and monitoring of Man-Machine systems: application to railway driving.

Summary The context of this thesis is the monitoring of man-machine systems, where the operator is the driver of a railway transport system. Our objective is to improve the safety of the system by preventing and avoiding factors that can increase the risk of human error. Two major problems are identified: the characterization aspect, or how to determine the indicative and discernible phases of the driving activity, and the representation aspect, or how to describe and codify the operator's driving actions and their repercussions on the railway system in a mathematical formalism allowing an unequivocal analysis. To solve these problems, we first propose a behavioral model of the human operator allowing to represent his control behavior in continuous time. In order to take into account the inter- and intra-individual differences of human operators, as well as the changes of situations, we propose a transformation of the initially presented behavioral model, in a new representation space. This transformation is based on the theory of hidden Markov chains, and on the adaptation of a particular pattern recognition technique. Then, we define a discrete time behavioral model of the human operator, allowing at the same time to represent his actions and to take into account errors and unexpected events in the work environment. This modeling is inspired by cognitive operator models. Both aspects allow the interpretation of observables in relation to reference situations. In order to characterize the global state of the human operator, different information is taken into consideration. This information is heterogeneous and subject to measurement uncertainties, requiring a robust data fusion procedure that is performed using a Bayesian network. Finally, the proposed modeling and fusion methodologies are used to design a reliable and non-intrusive vigilance system. This system allows the interpretation of driving behaviors and the detection of risky states of the driver (e.g. hypovigilance). The theoretical study was tested in simulation to verify its validity. Then, a feasibility study was carried out on experimental data obtained during experiments on the COR&GEST railway driving platform of the LAMIH laboratory. These results allowed to plan and to set up the experiments to be carried out on the future multimodal driving simulator "PSCHITT-PMR".