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Task Models for Supporting Function Allocation between Operators and Autonomous Systems: Application to Collision Avoidance Operations for Spacecraft

Fayollas, Camille and Martinie De Almeida, Célia and Palanque, Philippe and Fahssi, Racim Mehdi Task Models for Supporting Function Allocation between Operators and Autonomous Systems: Application to Collision Avoidance Operations for Spacecraft. (2016) In: AAAI 2016 Spring Symposium on Intelligent systems for supporting distributed human teamwork (AAAI-SS 2016), 21 March 2016 - 23 March 2016 (Stanford, CA, United States).

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Official URL: https://www.aaai.org/ocs/index.php/SSS/SSS16

Abstract

This position paper advocates that enhanced tasks description techniques can support the design of collaborative systems by supporting function allocation. This support can be useful for allocating functions between operators but also for migrating functions from operators to automation. Designing systems in such a way that as much functions as possible are automated has been the driving direction of research and engineering in aviation, space and more generally in computer science for many years. In the 90's many studies (e.g. (Palmer 1995) related to the notion of mode confusion) have demonstrated that fully automated systems are out of the grasp of current technologies and that additionally migrating functions (Boy 1998) from the operator to the system might have disastrous impact on operations both in terms of safety and usability. In order to be able to design automation with a hedonic view of the involved factors (safety, usability, reliability , …) a complete understanding of operator's tasks is required prior to considering migrating them to the system side or distributing them between a group of operators. This paper proposes a contribution for reasoning about multiuser (in-cluding automation)designs using a model-based approach exploiting refined collaborative task models. These models describe operations with enough details in order to reason about automation, function allocation and to rationalize the related designs. In this paper we present how such representations can support the assessment of alternative design options including automation. These contributions are exemplified in a multinational context of Spacecraft Collision Avoidance Systems.

Item Type:Conference or Workshop Item (Paper)
Additional Information:AAAI: Association for the Advancement of Artificial Intelligence
Audience (conference):International conference proceedings
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Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited On:08 Jun 2020 13:11

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