This toolbox provides map converters for OpenStreetMap (OSM), Lanelet / Lanelet2, OpenDRIVE, and SUMO to the CommonRoad (CR) format and for some formats vice versa. Additionally, a graphical user interface (GUI) is included, which allows one to efficiently create and manipulate CommonRoad maps and scenarios.
| Tool | Path | Functionality |
|---|---|---|
| OpenDRIVE <=> CR | crdesigner/map_conversion/opendrive |
Conversion from OpenDRIVE to CommonRoad and vice versa. |
| Lanelet/Lanelet2 <=> CR | crdesigner/map_conversion/lanelet2 |
Conversion from Lanelet2 to CommonRoad and from CommonRoad to Lanelet |
| OSM => CR | crdesigner/map_conversion/osm2cr |
Conversion from OSM to CommonRoad. |
| SUMO <=> CR | crdesigner/map_conversion/sumo_map |
Conversion from SUMO to CommonRoad and vice versa. |
| OpenDRIVE => Lanelet/Lanelet2 | crdesigner/map_conversion/map_conversion_interface |
Conversion from OpenDRIVE to Lanelet2 |
| Map Verification and Repairing | crdesigner/verification_repairing |
Verification and Repairing of CommonRoad maps. |
| CR Scenario Designer GUI | crdesigner/ui/gui |
Multi-functional GUI for map conversion and scenario creation/editing. |
We have tested the toolbox with Python 3.9, 3.10, and 3.11. The toolbox works under Linux. Below we present two ways of installing the CommonRoad Scenario Designer:
- Only using the CommonRoad Scenario Designer, e.g.,the GUI or integrating the scenario designer APIs into your code
- Developing code for the CommonRoad Scenario Designer
The recommended way of installation if you only want to use the scenario designer (i.e., you do not want to work with the code directly) is to use the PyPI package:
pip install commonroad-scenario-designerFirst, clone the repository. The usage of Poetry is recommended. Poetry can be installed using:
curl -sSL https://install.python-poetry.org | python3 -Create a new Python environment:
poetry shell
poetry install --with tests,docs,tutorialsWe recommend to use PyCharm (Professional) as IDE.
- Could not load the Qt platform plugin “xcb” in “” even though it was found: Error seems to be a missing package - either libxkbcommon-x11 or libxcb-xinerama0 (both can be installed by
sudo apt install [package_name]). See for reference here
We provide different types of usage for the CommonRoad Scenario Designer. Subsequently, we present for each component the different usage methods.
The recommended aspect ratio is 16:9 with a scaling of 100%. Within the GUI, you can also execute the different converters. The GUI can either be activated via a Python API, command line, or executing a Python script.
First you need to activate your python environment with the installed dependencies. Afterward, you can start the CommonRoad Scenario Designer and the GUI will open:
$ python crdesigner/ui/gui/start_gui.pyThe GUI can be started from command line via the following two options:
$ crdesigner
$ crdesigner guiNote that you have to activate first the Python environment in which the CommonRoad Scenario Designer is installed.
You can also execute a map conversion via the commandline interface, e.g.,
crdesigner --input-file /input/path/l2file.osm --output-file /output/path/crfile.xml lanelet2cr.
The output of crdesigner --help looks as follows:
Usage: crdesigner [OPTIONS] COMMAND [ARGS]...
Toolbox for Map Conversion and Scenario Creation for Autonomous Vehicles
Options:
--input-file PATH Path to OpenDRIVE map
--output-file PATH Path where CommonRoad map should be stored
--force-overwrite / --no-force-overwrite
Overwrite existing CommonRoad file
[default: force-overwrite]
--author TEXT Your name
--affiliation TEXT Your affiliation, e.g., university, research
institute, company
--tags TEXT Tags for the created map
--install-completion [bash|zsh|fish|powershell|pwsh]
Install completion for the specified shell.
--show-completion [bash|zsh|fish|powershell|pwsh]
Show completion for the specified shell, to
copy it or customize the installation.
--help Show this message and exit.
Commands:
crlanelet2
crsumo
gui
lanelet2cr
odrcr
osmcr
sumocr
odrlanelet2`You can execute the different converters either via command line, calling them within your Python program via an API, or the GUI.
The main APIs to execute the pure conversions are located under crdesigner/map_conversion/map_conversion_interface.py.
For many conversions we provide further APIs, e.g., for downloading a map from OSM.
The GUI provides a toolbox with which contains functionality to load maps given in formats other the CommonRoad format and to convert CommonRoad maps to other formats or the other formats to the CommonRoad format.
Provides the functionality to save the animation of the scenario as a mp4 file.
For error: "MovieWriter ffmpeg unavailable; using Pillow instead." try to install ffmpeg. This should solve the problem.
sudo apt-install ffmpegWhen converting OSM maps, missing information such as the course of individual lanes is estimated during the process. These estimations are imperfect (the OSM maps as well) and often it is advisable to edit the scenarios by hand via the GUI.
We also provide tutorials demonstrating how the different map converter APIs can be used. The tutorials include a jupyter notebook and exemplary Python scripts for each conversion.
To generate the documentation from source, first install the necessary dependencies with pip:
mkdocs serveThe documentation can be accessed by opening public/index.html.
The titles of module pages have to be set manually!
The full documentation of the API and introducing examples can also be found here.
A detailed overview about the changes in each version is provided in the Changelog.
This release (v0.9.3) is still a BETA version. In case you detect a bug or you want to suggest a new feature, please report it in our forum. If you want to contribute to the toolbox, you can also post it in the forum.
Responsible: Sebastian Maierhofer, Sebastian Mair Contribution (in alphabetic order by last name): Daniel Asch, Hamza Begic, Mohamed Bouhali, Florian Braunmiller, Tim Dang, Setenay Eryasar, Behtarin Ferdousi, Maximilian Fruehauf, Marcus Gabler, Fabian Hoeltke, Julian Hohenadel, Tom Irion, Aaron Kaefer, Anton Kluge, David Le, Gustaf Lindgren, Sarra Ben Mohamed, Benjamin Orthen, Luisa Ortner, Louis Pröbstle, Benedikt Reinhard, Maximilian Rieger, Nikolaos Sotirakis, Til Stotz, Stefan Urban, Max Winklhofer
We gratefully acknowledge partial financial support by
- DFG (German Research Foundation) Priority Program SPP 1835 Cooperative Interacting Automobiles
- BMW Group within the Car@TUM project
- Central Innovation Programme of the German Federal Government under grant no. ZF4086007BZ8
If you use our code for research, please consider to cite our papers:
@inproceedings{Maierhofer2023,
author = {Maierhofer, Sebastian and Ballnath, Yannick and Althoff, Matthias},
title = {Map Verification and Repairing Using Formalized Map Specifications},
booktitle = {2023 IEEE International Conference on Intelligent Transportation Systems (ITSC)},
year = {2023},
pages = {},
abstract = {Autonomous vehicles benefit from correct maps to participate in traffic safely, but often maps are not verified before their usage.
We address this problem by providing an approach to verify and repair maps automatically based on a formalization of map specifications in higher-order logic.
Unlike previous work, we provide a collection of map specifications.
We can verify and repair all possible map parts, from geometric to semantic elements, e.g., adjacency relationships, lane types, road boundaries, traffic signs, and intersections.
Due to the modular design of our approach, one can integrate additional logics.
We compare ontologies, answer set programming, and satisfiability modulo theories with our higher-order logic verification algorithm.
Our evaluation shows that our approach can efficiently verify and repair maps from several data sources and of different map sizes.
We provide our tool as part of the CommonRoad Scenario Designer toolbox available at commonroad.in.tum.de.},
}
@inproceedings{Maierhofer2021,
author = {Sebastian Maierhofer, Moritz Klischat, and Matthias Althoff},
title = {CommonRoad Scenario Designer: An Open-Source Toolbox for Map Conversion and Scenario Creation for Autonomous Vehicles},
booktitle = {Proc. of the IEEE Int. Conf. on Intelligent Transportation Systems },
year = {2021},
pages = {3176-3182},
abstract = {Maps are essential for testing autonomous driving functions. Several map and scenario formats are
available. However, they are usually not compatible with each other, limiting their usability.
In this paper, we address this problem using our open-source toolbox that provides map converters
from different formats to the well-known CommonRoad format. Our toolbox provides converters for
OpenStreetMap, Lanelet/Lanelet2, OpenDRIVE, and SUMO. Additionally, a graphical user interface is
included, which allows one to efficiently create and manipulate CommonRoad maps and scenarios.
We demonstrate the functionality of the toolbox by creating CommonRoad maps and scenarios based on
other map formats and manually-created map data.},
}
If you use the OpenDRIVE to CommonRoad conversion for your paper, please consider to additionally cite the corresponding paper:
@inproceedings{Althoff2018b,
author = {Matthias Althoff and Stefan Urban and Markus Koschi},
title = {Automatic Conversion of Road Networks from OpenDRIVE to Lanelets},
booktitle = {Proc. of the IEEE International Conference on Service Operations and Logistics, and Informatics},
year = {2018},
pages = {157--162},
abstract = {Detailed road maps are an important building block for autonomous driving. They accelerate creating a
semantic environment model within the vehicle and serve as a backup solution when sensors are occluded
or otherwise impaired. Due to the required detail of maps for autonomous driving and virtual test
drives, creating such maps is quite labor-intensive. While some detailed maps for fairly large regions
already exist, they are often in different formats and thus cannot be exchanged between companies and
research institutions. To address this problem, we present the first publicly available converter from
the OpenDRIVE format to lanelets—both representations are among the most popular map formats.
We demonstrate the capabilities of the converter by using publicly available maps.},
}