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Modélisation et prédiction des franchissements de barrières basées sur l'utilité espérée et le renforcement de l'apprentissage : application à la conduite automobile

Abstract : Risk analysis in Human-machine system (HMS) has to take into account human errors to limit their occurrences or consequences. That’s why, HMS designers define many barriers in the HMS environment. However, these barriers may be removed by human operators. That’s why it’s necessary to integrate the barrier removal in HMS design in order to better their design. The best way that insures this integration is the barrier removal modelling and prediction. This work proposes two linear models of the barrier removal utility: a generic one and a specific one. They integrate the different criteria related to the human operator activity, the Benefits, Costs and potential Deficits associated to these criteria, the weights αi, βi, and γi, the erreors εαi, εβi and εγi and the sensibility threshold Δu. The modification of these two last model’s elements provides an amelioration of the barrier removal utility value and so the barrier removal prediction. This new barrier removal prediction method was applied to the car driving domain. Its results are very interesting
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https://hal-uphf.archives-ouvertes.fr/tel-03001761
Contributor : Marie Zoia <>
Submitted on : Thursday, November 12, 2020 - 2:56:25 PM
Last modification on : Saturday, November 28, 2020 - 3:21:15 AM

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  • HAL Id : tel-03001761, version 1

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Abir Chaali-Djelassi. Modélisation et prédiction des franchissements de barrières basées sur l'utilité espérée et le renforcement de l'apprentissage : application à la conduite automobile. Automatique / Robotique. Université de Valenciennes et du Hainaut-Cambrésis, 2007. Français. ⟨NNT : 2007VALE0009⟩. ⟨tel-03001761⟩

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