A survey on motion prediction and risk assessment for intelligent vehicles

Stéphanie Lefèvre (1, 2) , Dizan Vasquez (1) , Christian Laugier (1)

1 E-MOTION - Geometry and Probability for Motion and Action
2 LBNL - Lawrence Berkeley National Laboratory [Berkeley]

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.

Domaines: Informatique [cs]

Stéphanie Lefèvre, Dizan Vasquez, Christian Laugier. A survey on motion prediction and risk assessment for intelligent vehicles. ROBOMECH Journal, 2014, 1 (1), pp.1. ⟨10.1186/s40648-014-0001-z⟩. ⟨hal-01053736⟩