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Évaluation multidimensionnelle et dynamique de la maitrise de la situation par l’opérateur : création d’un indicateur temps réel de charge mentale pour l’activité de supervision de drones

Abstract : The evolution of technology has resulted in the emergence of increasingly complex and automated systems. In dynamic situations, the activity of the operator is now more centred on supervision than on execution. These situations are characterized by complexity, uncertainty, partial control and a significant risk of losing control of the situation. The main objective of the work presented in this manuscript is to create a synthetic mental workload indicator, which will be used to trigger a reallocation of functions in real time. The ultimate goal is to enable the operator to better regulate his/her mental workload and to help him/her maintain or regain control of the situation. This work is applied to the supervision activity of a drone swarm studied on a simulation platform (the SUSIE platform). We have revisited and combined the model of Hart and Staveland (1988), which considers the mental workload as a multidimensional construct and that of Sperandio (1971), which focuses on the regulation of activity. This led us to propose a dynamic and three-dimensional model (based on the analysis of the constraints, the effects of the workload on the task and the operator, and the regulations), on which we relied to build a creative approach of a synthetic mental workload indicator. This process is divided into four stages. The first consists in carrying out an analysis of the task following the methodology of Sperandio (1988), to define and identify the descriptors of the mental workload according to the three categories of our dynamic and three-dimensional model. The second step is based on the realization of an experiment, which aims to validate or exclude the identified indicators, per their sensitivity to variations in mental workload (as defined by Cegarra et Chevalier (2008)). The results show in particular that the pupillary diameter and the observation of the regulations allow an appreciable measurement. The third step aims to create a synthetic indicator of mental load by merging the chosen indicators by using Bayesian networks and fuzzy logic. Finally, the last phase supports the design of a dynamic allocation of functions, triggered from the synthetic indicator of mental workload. A second experiment was carried out to evaluate the contribution of reallocation. It shows that the aid allows the operator to better regulate his activity; it modifies the task workload (constraint), but does not reduce the mental workload.
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Alexandre Sviatoslave Kostenko. Évaluation multidimensionnelle et dynamique de la maitrise de la situation par l’opérateur : création d’un indicateur temps réel de charge mentale pour l’activité de supervision de drones. Interface homme-machine [cs.HC]. Université de Bretagne Sud, 2017. Français. ⟨NNT : 2017LORIS438⟩. ⟨tel-01677692⟩

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