Human modeling in a driver analyzing context: challenge and benefit

In the past years, driver analyzing has become a field of increasing interest. Within this topic, camera based as well as camera free systems are in the scope of researchers all over the world with the overall goal to detect, for example, critical driver states like drowsiness or distraction. Unfortunately, there are yet no comprehensive models for understanding the driver and his states in the automotive context. Therefore, we present a user model tailored to automotive needs. This model allows us to understand the driver in the automotive environment and to set up a general architecture from which we can decide on necessary input information for detecting a certain driver state.