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Modelling of cognitive activity during normal and abnormal situations using Object Petri Nets, application to a supervision system

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Abstract

This article presents a method for the modelling of cognitive activity using Object Petri Nets. The method includes the recognition of the various classes of situation (normal and abnormal) which human operators are likely to meet whilst performing their tasks. Each of these classes is described according to the characteristics of the state of the system. We will present the various mental representations used during the control/command activity according to the main aims set by the operator. The examples given come from a project dealing with the integration of a a supervision system in a railway traffic regulation room.

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Acknowledgements

The authors would like to thank the SNCF, and also the FEDER, the GRRT and the Nord-Pas-de Calais regional authorities which have provided support for this research (SART and NIPO projects).

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  1. Laboratoire d’Automatique, de Mécanique et d’Informatique industrielles et Humaines LAMIH UMR CNRS 8530, Le Mont-Houy University of Valenciennes and Hainaut-Cambrésis, Valenciennes Cedex 9, 59313, France

    H. Ezzedine & C. Kolski

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  1. H. Ezzedine
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  2. C. Kolski
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Correspondence to C. Kolski.

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Ezzedine, H., Kolski, C. Modelling of cognitive activity during normal and abnormal situations using Object Petri Nets, application to a supervision system. Cogn Tech Work 7, 167–181 (2005). https://doi.org/10.1007/s10111-005-0184-4

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  • DOI: https://doi.org/10.1007/s10111-005-0184-4

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