Quick Start

Using METS-R in Docker (Recommended)

The recommended way to run METS-R is through the Docker-based HPC module, which packages the simulator and all its dependencies into a self-contained container and requires no Java or Eclipse setup.

Prerequisites: Install Docker and Python ≥ 3.10.

Clone the METS-R HPC repository:

git clone https://github.com/umnilab/METS-R_HPC.git
cd METS-R_HPC

Create a Python environment and install all requirements:
```
pip install -r requirements.txt
```
Build the PostgreSQL Docker image (used for logging simulation outputs):
```
cd docker
docker build -t postgres postgres
cd ..
```
Open interactive_example.ipynb in VS Code or any Jupyter-compatible IDE and run each cell in order. The notebook walks through starting the Docker containers, connecting to the simulator, and exercising the step, query, and control APIs end-to-end.

Note

On Windows, ensure that the Host Networking feature is enabled in Docker Desktop settings (Settings → Resources → Network → Enable host networking).

Several APIs are developed to query and control the simulation. See Interactive APIs for more details.

Standalone mode

Download and install Eclipse IDE with Repast Simphony 2.7 from here.

Clone the METS-R repository using git to a target folder.

git clone https://github.com/umnilab/METS-R_SIM.git

Open Eclipse and go to File -> Open Projects from File System…
In the Import Projects from File System or Archive window click on Directory and open the METS_R directory you cloned in Step 2.
Check METS_R and click Finish. This should open the METS-R SIM project in Eclipse as shown in the following figure.

Load the METS_R SIM project in Eclipse
Go to the laucher folder in the project explorer, then right click METS_R Model.launch and select Run as -> METS-R Model to start the simulation.
You should see the below Repast Symphony simulation window (After specifying the first time, you can also use the Run button in the Eclipse toolbar).
Click on the Start Run button in the pop-up window to begin the simulation.
The simulation outputs can be found in the agg_output folder, and the vehicle trajectories is in the trajectory_output folder.
You can check the configuration file (METS_R/data/Data.properties) for options available in the simulation.

Synchronized mode

You can run the synchronized mode in the following ways:

Interactive mode

Complete the Docker setup steps 1–3 in the Using METS-R in Docker section above.
Open interactive_example.ipynb in VS Code or another Jupyter-compatible IDE.
Run each cell one by one.

Co-simulation mode with CARLA

Complete the Docker setup steps 1–3 in the Using METS-R in Docker section above.
Update carla_dir in configs/run_cosim_CARLAT5.json to point to your local CARLA installation. The carla Python package version must match your CARLA build (tested with CARLA 0.9.15).
Run python cosim_example.py -r configs/run_cosim_CARLAT5.json

More demand scenarios

More demand scenarios for the NYC network can be downloaded from here. You just need to copy this to data\ under the METS-R SIM folder.