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The safety of vehicle driving is within the focus of automotive development. In this work, an approach realizing cognitive awareness is introduced for automotive applications. The advantage of the approach is that the underlying Situation-Operator-Modeling (SOM) concept, can be applied to autonomous driving assuming that changes in the real world are to be considered and understood as a sequence of effects modeled by scenes and actions. For the representational level as part of the cognitive awareness approach, the SOM is used to model and structure the complex scenes of the driver-vehicle-environment interactions in general. First, the scene is modeled as a situation consisting of a group of characteristics, and the set of actions which are performed by the driver are specified and modeled as operators. In this work, passing maneuvers on highways are chosen as example.

In contrast to driver assistance systems focused on the vehicle-navigation or stabilization problems, the study of the loop-oriented interaction between driver, vehicle, and environment has been focused in the last years. The core of the proposed approach is the Situation-Operator-Modeling (SOM), which assumes that changes in the parts of the real world to be considered are understood as a sequence of effects modeled by scenes and actions. Based on SOM approach, the logic of interaction between the driver, the vehicle, and the environment can be formalized for supervision of the drivers' behaviors in a real car. Based on a general model of driving in combination with driver-vehicle-interaction developed in previous works, the personalization and individualization of the human driver model is focused.