Abstruct-The availability of a digital driver behavior model during emergency situations constitutes a major breakthrough dealing with active safety system tuning. This article presents a modeling approach based on an input-output system (initial conditions-driver's actions). The starting point of our work is a behavioral database gathered from a track experiment with common drivers. Subjects are confronted with the sudden braking of n released trailer, which they followed for n while. Our objective i s to predict driver's actions following a set of initial conditions (distance to collision, speeds, and friction). The core of our model is an inference system based on uugmenfed n u h Bayesian network. This article outlines the various stages leading to the construction of this model. It discusses its robustness using another database.
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