Strategies for Automated Updating of Road Networks for Driving Simulations

This master thesis deals with the problem of updating complex road networks for driving simulations. These road networks differ a lot from the ones which are, for example, used in navigation services. So far there is no applicable solution for an automated or partially automated update of these road networks and in this master thesis strategies for this process are developed. However, road networks for driving simulations are very important for the tests of new technologies before equipping them to real vehicles etc. and testing them in the real world. So it is crucial to have close to reality models of road environments in which these tests can be performed under safe and reproducible conditions. To supply current versions of road networks for these tests, the road networks have to be updated. Therefore, alterations between an existing and a new road network have to be identified. Such alterations can be of three different types: geometrical, topological, and semantic. Furthermore, new features can also be added to an existing road network or existing features may be removed. This requires the matching of corresponding road features first. As altered features differ from their former state, an identification can sometimes only work by comparing several attributes of the features at once. When the alterations could be identified, they have to be merged in the third and last step of the updating process. The development of these three steps is the major part of this master thesis. They are described and explained in theory but also implemented as a proof of concept. In two case studies the implementation is tested and their results are the basis for the final discussion and conclusion