The MATSim Open Kelheim Scenario

About this project

This repository provides an open MATSim transport model for Kelheim, provided by the Transport Systems Planning and Transport Telematics group of Technische Universität Berlin. It was developed as part of the KelRide project and thus funded by the German Federal Minstery for Digital and Transport.

This scenario contains a 25pct sample of Kelheim and its surrounding area; road capacities are accordingly reduced. The scenario is calibrated taking into consideration the traffic counts, modal split and mode-specific trip distance distributions.

Licenses

The MATSim program code in this repository is distributed under the terms of the GNU General Public License as published by the Free Software Foundation (version 2). The MATSim program code are files that reside in the src directory hierarchy and typically end with *.java.

The MATSim input files, output files, analysis data and visualizations are licensed under a Creative Commons Attribution 4.0 International License.
MATSim input files are those that are used as input to run MATSim. They often, but not always, have a header pointing to matsim.org. They typically reside in the input directory hierarchy. MATSim output files, analysis data, and visualizations are files generated by MATSim runs, or by postprocessing. They typically reside in a directory hierarchy starting with output.

Other data files, in particular in original-input-data, have their own individual licenses that need to be individually clarified with the copyright holders.

The input plans (person transport demand) for this project were generated based on data provided by Senozon AG.

Note (where to find input and output)

Handling of large files within git is not without problems (git lfs files are not included in the zip download; we have to pay; ...). In consequence, large files, both on the input and on the output side, reside at the public matsim-kelheim data repo.

Run the MATSim Kelheim scenario

The Kelheim scenario has a command line interface providing the following options:

It can be used by using either of these methods:

... using an IDE, e.g. Eclipse, IntelliJ - Alternative 1: use cloned/downloaded matsim-kelheim repository

(Requires either cloning or downloading the repository.)

1. Set up the project in your IDE.
2. Make sure the project is configured as maven project.
3. Run the JAVA class src/main/java/org/matsim/run/RunKelheimScenario.java with the following program argument run.
   1. Add '--1pct' for test runs with a smaller sample size. Be aware that the model is calibrated with 25 pct, and outputs for 1 pct might be a little off.
4. "Open" the output directory. You can drag files into VIA as was already done above.
5. Edit the config file or adjust the run class. Re-run MATSim.

... using a runnable jar file

(Requires either cloning or downloading the repository and java)

1. Open the cmd and go to your project directory
2. Build the scenario using ./mvnw package. Add the option -DskipTests=true in order to skip tests and speed up the process.
3. There should be a file directly in the matsim-kelheim directory with name approximately as matsim-kelheim-3.x-SNAPSHOT-<commitId>.jar.
4. Run this file from the command line using java -jar matsim-kelheim-3.x-SNAPSHOT-<commitId>.jar --help to see all possible options.
   1. For example, one can disable lanes or run smaller sample sizes using the available options
5. Start this scenario using the default config by running java -jar matsim-kelheim-3.x-SNAPSHOT-<commitId>.jar.
   1. If you want to run the scenario somewhere else, e.g. on a computation cluster, make sure to not only copy the jar but also the 'input' directory and put it right next to the jar.
6. "Open" the output directory.
   1. You can drag files into VIA as was already done above.
   2. You can also browse the output directory on vsp.berlin/simwrapper and analyse some of your results with interactive dashboards.

Results and analysis

Here are the most common ways to analyse and visualize the results (and inputs):

1. Simunto VIA
2. SimWrapper
   1. (use Google for the best experience)
   2. Browse your local output directory or the public matsim-kelheim data repo
   3. Explore and create many interactive visualisations and dashboards
3. Analyse the output .csv tables using the R language and the matsim-r package

If you have questions, feel free to contact us (VSP) any time :)

More information

For more information about MATSim, see here: https://www.matsim.org/

Internal documentation

Internal documentation can be found here: https://docs.google.com/document/d/1xOkHVUKVLrtliVS4Y8ITz6zswQE6BG2-Cdmhw-HKgQ/edit?usp=drivelink