Driving at night time increases the risk of accidents because the driver's perception is reduced to the limited area of the environment which is illuminated by the car's head lights. In the study presented in this paper, the tool Vehicle in the Loop (VIL) is used the first time to research the potential of a new light function. VIL is a Virtual Reality application and simulation setup which allows for testing driver assistance systems in critical driving situations while driving a real car, but without the risk of collisions with real objects. VIL is based on the Virtual Test Drive (VTD) simulation software. The Active Safety Light is an advanced light functionality which illuminates the potential escape path a driver should take in order to avoid an imminent accident. The two main results of this first field study are, that VIL is suitable to study advanced light functions and that the Active Safety Light supports the driver in critical situations. The driver reacts nearly 60 ms faster and the situation is estimated as more critical so that the driver brakes instinctively harder, i.e. the break pressure is increased by almost a factor of two.

Abstract-In this paper, it is shown that synthetic images can be used to test specific use cases of a lane tracking algorithm which has been developed by Audi AG. This was achieved by setting up a highly configurable and extendable simulation framework "Virtual Test Drive". The main components are a traffic simulation, visualization and a sensor model which supplies ground truth data about the street lanes. Additionally, the visualization is used to generate synthetic camera sensor data. The testbed also contains a realistic driving dynamics simulation and a real image processing soft ECU (which is represented as a standard PC in the early development stages). One of the modules on the image processing ECU is a lane tracking algorithm. The algorithm is designed to calculate the transition curves while driving. This information can be used as input for driving assistance functions, e.g. lane departure warning. By running the lane tracker on a synthetic image it is possible to compare the results of the lane tracker with the ground truth data provided by the simulation. In this particular case, the information has been used to test and optimize parts of the systems by using specific and determined scenarios in the simulation.