Development of a concept for asynchronous sensor data fusion for future driver assistance systems (Diplomarbeit)
Numerous driver assistance systems require information about the vehicle's surroundings. Robust vehicle environment perception, which is necessary for applications such as highly automated and autonomous driver assistance system, is guaranteed by asynchronous sensors with complementary features and overlapping field of views. This thesis is about the investigation and development of algorithms and approaches for track-to-track fusion within a high-level sensor data fusion architecture for highly automated driving applications. Algorithms which are already known in the literature are studied within a simulation environment to evaluate the quality of their results and usability in practical applications. Additionally, these algorithms are adapted to the automotive environment and the most promising algorithm is integrated into an architecture within a vehicle in order to evaluate the developed fusion concept using real sensor data. The goal of this thesis is to enable 360 surround environment perception and tracking using an underlying diverse sensor configuration.