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Cooperation and learning to increase the autonomy of ADAS

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Abstract

This paper discusses on the cooperation and the learning processes to increase the autonomy of a human–machine system or an artificial or human agent. The autonomy is defined as the capacity for a system or an agent to fend alone. It is described in terms of competences and the limits of these competences. Cooperation and learning aim then at increasing the competences or managing the system limits. The management of the autonomy is detailed through different structures of cooperation. It concerns the sharing control between systems or between agents in order to recover their limits. Different classes of learning processes are proposed: the mimicry-based approaches, the dysfunction-based ones, and the wait-and-see-based ones. Advanced Driver Assistance Systems (ADAS) are usually designed integrating cooperation characteristics. Two case studies about the use of cooperative ADAS are then proposed. They are hypothetical scenarios that are discussed to introduce possible future ADAS perspective implementing competences such as learning or cooperative learning.

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Acknowledgments

The present research work has been supported by the International Campus on Safety and Intermodality in Transportation the European Community, the Délégation Régionale à la Recherche et à la Technologie, the Ministère de l’Enseignement Supérieur et de la Recherche, the Région Nord Pas de Calais and the Centre National de la Recherche Scientifique, the Scientific Research Group on Supervisory, Safety and Security of Complex Systems, the European Research Group on Human–Machine Systems in Transportation and Industry: the authors gratefully acknowledge the support of these institutions.

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Vanderhaegen, F. Cooperation and learning to increase the autonomy of ADAS. Cogn Tech Work 14, 61–69 (2012). https://doi.org/10.1007/s10111-011-0196-1

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