Abstract: A method of automatically switching a turn indicator on a vehicle on or off, whereby ambient data about the vehicle is detected for determining the location of the vehicle. On the basis of this ambient data, changes in lane and/or direction of travel are determined. Before a change in lane or direction of travel, the turn indicator is turned on and turned off after changing lanes and/or direction of travel.

Abstract: A system installed in a motor vehicle for inferring a vehicle operator's stress level from body sensors and from environmental data related to the position and operation of the vehicle. The system functions in a training phase using machine learning techniques to derive a model of an individual operators stress reaction to the environment in which the vehicle is operated and, using the results of this training phase, the system is subsequently used to predict stress levels to be expected when certain traffic conditions are imminent based on a projection of the driver's physiolocial state. The result of this prediction of stress level for the individual driver is used to control or warn the driver with respect to operation and scheduling of attention diverting devices such as cellular phones.

Abstract: A system installed in a motor vehicle for inferring a vehicle operator's stress level from body sensors and from environmental data related to the position and operation of the vehicle. The system functions in a training phase using machine learning techniques to derive a model of an individual operators stress reaction to the environment in which the vehicle is operated and, using the results of this training phase, the system is subsequently used to predict stress levels to be expected when certain traffic conditions are imminent based on a projection of the driver's physiolocial state. The result of this prediction of stress level for the individual driver is used to control or warn the driver with respect to operation and scheduling of attention diverting devices such as cellular phones.

Abstract: A method and a device for detecting road users and obstacles on the basis of camera images, in order to determine their distance from the observer and to classify them. In a two-step classification, potential other parties involved in a collision are detected and identified. In so doing, in a first step, potential other parties involved in a collision are marked in the image data of a mono-image camera; their distance and relative velocity are subsequently determined so that endangering objects can be selectively subjected to a type classification in real time. By breaking down the detection activity into a plurality of steps, the real-time capability of the system is also rendered possible using conventional sensors already present in the vehicle.