ASAM OpenDRIVE with CityGML

For testing and The process of determining that a system performs and meets the needs for identified end users.Validation of advanced driver assistant systems and automated driving Is the process of imitation of the behavior of a modeled real-world system over time.Simulation is used. The complex systems under test do not only need precise and detailed modeling of the road but also a growing amount of information about the environment, too. ASAM OpenDRIVE is fulfilling the task for the road description becoming a de-facto A public specification, which has been developed by experts in a defined consensus-driven development process and was released by officials that represent a significant share of the industry for which it is targeted, giving the specification the necessary legitimacy to be called a 'Standard'.Standard in the automotive industry.

Instead of expanding ASAM OpenDRIVE into a full environmental model, the paper investigates how its precise road-network logic can be combined with the semantically rich 3D environments of OGC CityGML.

The project compared how both standards represent buildings, traffic lights, road markings, terrain, and adjacent areas. It then developed and tested an object-level linking concept using a proof-of-concept dataset, including data conversion, identifier mapping, external references, compression, spatial queries, glTF derivation, and an initial integration with Esmini.

The proof of concept showed that ASAM OpenDRIVE can remain the primary source for driving-relevant road information while applications retrieve richer geometry and environmental data from CityGML when needed. The paper recommends optional object-level linking as the best trade-off, adding access to digital twin data without breaking compatibility with existing ASAM OpenDRIVE datasets and tools.

Concept PAPER