A survey on motion prediction and risk assessment for intelligent vehicles

Stéphanie Lefèvre 1, 2, * Dizan Vasquez 1 Christian Laugier 1
* Auteur correspondant
1 E-MOTION - Geometry and Probability for Motion and Action
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : With the objective to improve road safety, the automotive industry is moving toward more “intelligent” vehicles. One of the major challenges is to detect dangerous situations and react accordingly in order to avoid or mitigate accidents. This requires predicting the likely evolution of the current traffic situation, and assessing how dangerous that future situation might be. This paper is a survey of existing methods for motion prediction and risk assessment for intelligent vehicles. The proposed classification is based on the semantics used to define motion and risk. We point out the tradeoff between model completeness and real-time constraints, and the fact that the choice of a risk assessment method is influenced by the selected motion model.
Type de document :
Article dans une revue
ROBOMECH Journal, Springer, 2014, 1 (1), pp.1. 〈10.1186/s40648-014-0001-z〉
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Soumis le : vendredi 1 août 2014 - 13:22:49
Dernière modification le : jeudi 11 octobre 2018 - 08:48:02
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Stéphanie Lefèvre, Dizan Vasquez, Christian Laugier. A survey on motion prediction and risk assessment for intelligent vehicles. ROBOMECH Journal, Springer, 2014, 1 (1), pp.1. 〈10.1186/s40648-014-0001-z〉. 〈hal-01053736〉

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