Testing of Image Processing Algorithms on Synthetic Data

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 ldquovirtual test driverdquo. 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.