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TAPAS-SUMO-Coupling (tsc)

Combining traffic demand estimation with microscopic traffic simulation

Requirements

Git

Make sure you have git-lfs on your system (sudo apt-get install git-lfs) and activated for your user (git lfs install).

Python

The scripts should work with Python 2.7 and Python 3.5 or later. The psycopg2 adapter is needed for database communication. It is strongly recommended to have the rtree module which speeds up several lookup procedures and pandas if you need GTFS import. (sudo apt-get install python-psycopg2 python-rtree python-pandas and/or sudo apt-get install python3-psycopg2 python3-rtree python3-pandas). This can also be done using pip (tested with RedHat EL 7): pip install --user wheel -r requirements.txt Wheel is needed for rtree installer

SUMO

You need to have a working SUMO installation and your environment variable SUMO_HOME needs to be set. On ubuntu sudo apt-get install sumo should suffice.

Installing

  1. Clone this repo git clone https://github.com/DLR-TS/tsc (do another pull if you cloned without having lfs active).
  2. Copy postgres_template.tsccfg (e.g. to postgres.tsccfg) and enter the database connection details (server, user, passwd)
  3. Run pip install --user . (developers may want to add -e here for an editable install, this requires pip>=23.0)
  4. Run tsc_install -c postgres.tsccfg
  5. (optional) Testfield Lower Saxony git clone https://github.com/DLR-TS/sumo-scenarios and tsc_install -c postgres.tsccfg -p ../sumo-scenarios/. This will try to install other scenarios as well but you can safely ignore the corresponding warnings.

The installation needs the database connection only if you plan to use scenarios with (Germany wide) background traffic. If you don't need it, you can omit the -c postgres.tsccfg part.

Running

  1. Prepare the credentials file postgres.tsccfg as described in section Installing
  2. Run tsc_main -c postgres.tsccfg --daemon

The --daemon-flag lets the tsc loop look for new simulation requests. Alternatively you can run a specific simulation key like this: tsc_main --sim-key 2021y_06m_04d_11h_04m_34s_855ms -c postgres.tsccfg.

If you want to override certain simulation parameters on the command line use the option --sim-param for instance --sim-param SUMO_TEMPLATE_FOLDER:siemensbahn,SUMO_DESTINATION_FOLDER:siemensbahn,SUMO_MODES:'0;1;2;3;5;6;261;517'. For a list of available parameters have a look at the relevant database table public.simulation_parameters or at constants.py (the SP class).

Testing

This requires texttest to be installed (using pip install --user texttest or the windows installer). To run the tests you will either need a running postgresql database or you will need to configure your sqlite installation such that it can use the spatialite extension. Most of the time it suffices to install mod_spatialite (sudo apt-get install libsqlite3-mod-spatialite). It is very likely that this works only with python3. If you have everything installed run one of the scripts in the test directory which should fire up the texttest GUI and allow you to run selected or all tests. Please be aware that you cannot run the tests in parallel if you use PostGreSQL because they all access the same database.

Setting up a new scenario

The tsc_install script sets up a scenario template for every subdirectory in its data dir. So the first step to add a new scenario is to add a new subdirectory which needs at least

  1. A SUMO network named net.net.xml.gz.
  2. A definition of vehicle types named vtypes.xml While the tsc tooling allows a fine grained configuration those two files are everything you need to get started, more details are given below.

The network

The tsc_install script supports the creation of a network from OpenStreetMap data. If you provide one or multiple template_gen*.netccfg file(s) the script will execute them in lexical order and the last call should generate the needed net.net.xml.gz. This way it is possible to rebuild the network on every new installation. If you do so you need to provide the input (OSM XML) files in your data directory and let the netccfg refer to them.

The vehicle types

TAPAS assigns a vehicle type to every vehicle which needs to be mapped (by it's name) to a SUMO vehicle type. The file vtypes.xml should simply list them with their properties including emission classes (if known).

Additional data

It may be useful to have additional files in a scenario (to be described)

  • Traffic assignment zones for suburban areas
  • landmarks to speed up routing

Furthermore you can define custom scripts (with the name setup.py) which get called in the installation process and can modify or generate the rquired inputs.