Improving driver's situation awareness.
Résumé
Initial training, which concludes by a driving license, is insufficient because new drivers do not know how to contextualize the learned procedures into effective practices. Our goal is to improve the driver's Situation Awareness, i.e. the way in which the driver perceives events in the environment, and the projection of their status in a close future. More precisely, our concern is the way in which the driver evaluates the criticality of a situation. First, we model drivers’ behavior along two approaches, that is, local and global approaches, in order to have a driver model as exhaustive as possible. Second, we model drivers in a twofold representation, a situation space (an objective representation given by a lattice) and a behavior space (a subjective representation given by a contextual graph). Scenarios connect the two representations. We present in this paper the results of a specific study on driver classification based on the two approaches.
Format du dépôt | Notice |
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Type de dépôt | Communication dans un congrès |
Titre |
en
Improving driver's situation awareness.
|
Résumé |
en
Initial training, which concludes by a driving license, is insufficient because new drivers do not know how to contextualize the learned procedures into effective practices. Our goal is to improve the driver's Situation Awareness, i.e. the way in which the driver perceives events in the environment, and the projection of their status in a close future. More precisely, our concern is the way in which the driver evaluates the criticality of a situation. First, we model drivers’ behavior along two approaches, that is, local and global approaches, in order to have a driver model as exhaustive as possible. Second, we model drivers in a twofold representation, a situation space (an objective representation given by a lattice) and a behavior space (a subjective representation given by a contextual graph). Scenarios connect the two representations. We present in this paper the results of a specific study on driver classification based on the two approaches.
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Auteur(s) |
Juliette Brézillon
1
, Patrick Brézillon
2
, Charles Tijus
3, 4
1
MALIRE -
Machine Learning and Information Retrieval
( 396897 )
- France
2
DECISION
( 394573 )
- France
3
CHART -
Cognitions Humaine et ARTificielle
( 104214 )
- Université Paris 8 Vincennes-Saint-Denis - 2 rue de la Liberté - 93526 Saint-Denis cedex
- France
4
LUTIN -
Laboratoire des Usages en Technologies d'Information Numériques
( 542056 )
- Cité des Sciences et de l'Industrie (Niveau -2), 30 avenue Corentin Cariou, 75019 Paris
- France
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Langue du document |
Anglais
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Source |
Proceedings of the Fourth International Workshop on Modeling and Reasoning in Context (MRC-2007)
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Vulgarisation |
Non
|
Actes |
Oui
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Comité de lecture |
Oui
|
Invité |
Non
|
Audience |
Internationale
|
Date de publication |
2007
|
Titre de la collection |
Computer Science Research Report
|
Volume |
112
|
Page/Identifiant |
61-74
|
Titre du congrès |
Fourth International Workshop on Modeling and Reasoning in Context (MRC-2007)
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Date début congrès |
2007-08-20
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Date fin congrès |
2007-08-24
|
Ville |
Roskilde
|
Pays |
Danemark
|
Domaine(s) |
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Éditeur commercial |
|
Mots-clés |
da
driver's
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