  High-definition road maps play a crucial role in the functionality and
verification of highly automated driving functions. These contain precise
information about the road network, geometry, condition, as well as traffic
signs. Despite their importance for the development and evaluation of driving
functions, the generation of high-definition maps is still an ongoing research
topic. While previous work in this area has primarily focused on the accuracy
of road geometry, we present a novel approach for automated large-scale map
generation for use in industrial applications. Our proposed method leverages a
minimal number of external information about the road to process LiDAR data in
segments. These segments are subsequently combined, enabling a flexible and
scalable process that achieves high-definition accuracy. Additionally, we
showcase the use of the resulting OpenDRIVE in driving function simulation.
