a road space model transformer library for OpenDRIVE, CityGML and beyond
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r:trån reads road network models in OpenDRIVE and transforms them to the virtual 3D city model standard CityGML.

This enables you to

• inspect your spatio-semantic road space models
• conduct further model transformations with tools like FME
• perform geospatial analyses on the 3D City Database
• deploy virtual globes
• load your models into a desktop GIS
• compare and validate your models with models from other data sources

📥 Datasets

Download some sample OpenDRIVE datasets of the city of Ingolstadt from the company 3D Mapping Solutions (initial registration required). Additionally, awesome-openx provides a list of further OpenDRIVE datasets.

🚀 Usage

In order to use r:trån you need JDK 11 or later. Download the prebuilt JAR executable from the releases section and make sure that you have at least a JVM 11. Run r:trån to ...

# … validate OpenDRIVE datasets
java -jar rtron.jar validate-opendrive ./input-opendrive ./output-reports

# … transform OpenDRIVE datasets to CityGML
java -jar rtron.jar opendrive-to-citygml ./input-opendrive ./output-citygml

R:trån recursively iterates over your OpenDRIVE input datasets and creates the same directory structure for the output folder.

👷 Building

Clone the repo and let gradle build it:

./gradlew shadowJar # build the uber-jar
cd rtron-cli/build/libs
java -jar rtron-*.jar

You're good to go 💪

🛠️ Contributing

r:trån was developed so that everyone can benefit from spatio-semantic road space models. Therefore, bug fixes, issue reports and contributions are greatly appreciated.

🎓 Research

If you are interested in the concepts and a first application of r:trån, have a look at our paper. Based on the consistent models now available in OpenDRIVE and CityGML, we generate several target formats for setting up a distributed environment simulation.

@article{SchwabBeilKolbe2020,
  title = {Spatio-Semantic Road Space Modeling for Vehicle{\textendash}Pedestrian Simulation to Test Automated Driving Systems},
  author = {Benedikt Schwab and Christof Beil and Thomas H. Kolbe},
  journal = {Sustainability},
  year = {2020},
  month = may,
  volume = {12},
  number = {9},
  pages = {3799},
  publisher = {MDPI},
  doi = {10.3390/su12093799},
  url = {https://doi.org/10.3390/su12093799}
}

Moreover, these papers may also be of interest:

• Detailed Streetspace Modelling for Multiple Applications: Discussions on the Proposed CityGML 3.0 Transportation Model
• Requirement Analysis of 3D Road Space Models for Automated Driving
• CityGML and the streets of New York - A proposal for detailed street space modelling

📝 License

r:trån is distributed under the Apache License 2.0. See LICENSE for more information.

🤝 Thanks

• Lutz Morich and AUDI AG for providing an awesome work environment within SAVe
• Prof. Thomas H. Kolbe, Bruno Willenborg and Christof Beil for support and feedback
• Claus Nagel for citygml4j
• JetBrains for Kotlin and their top-notch IDEs