This repository contains the code to create an open data synthetic population of the Île-de-France region around in Paris and other regions in France.
The main research reference for the synthetic population of Île-de-France is:
Hörl, S. and M. Balac (2020) Reproducible scenarios for agent-based transport simulation: A case study for Paris and Île-de-France, Arbeitsberichte Verkehrs-und Raumplanung, 1499, IVT, ETH Zurich, Zurich.
This repository contains the code to create an open data synthetic population of the Île-de-France region around in Paris and other regions in France. It takes as input several publicly available data sources to create a data set that closely represents the socio-demographic attributes of persons and households in the region, as well as their daily mobility patterns. Those mobility patterns consist of activities which are performed at certain locations (like work, education, shopping, ...) and which are connected by trips with a certain mode of transport. It is known when and where these activities happen.
Such a synthetic population is useful for many research and planning applications. Most notably, such a synthetic population serves as input to agent-based transport simulations, which simulate the daily mobility behaviour of people on a spatially and temporally detailed scale. Moreover, such data has been used to study the spreading of diseases, or the placement of services and facilities.
The synthetic population for Île-de-France can be generated from scratch by everybody who has basic knowledge in using Python. Detailed instructions on how to generate a synthetic population with this repository are available below.
Although the synthetic population is independent of the downstream application or simulation tool, we provide the means to create an input population for the agent- and activity-based transport simulation framework MATSim.
This pipeline has been adapted to many other regions and cities around the world and is under constant development. It is released under the GPL license, so feel free to make adaptations, contributions or forks as long as you keep your code open as well!
This pipeline fulfils to purposes: First, to create synthetic populations of French regions in CSV and GLPK format including households, persons and their daily localized activities. Second, the pipeline makes use of infrastructure data to generate the inputs to agent-based transport simulations. These steps are described in the following documents:
- How to create a synthetic population of Île-de-France
- How to run a MATSim simulation of Île-de-France
Furthermore, we provide documentation on how to make use of the code to create popuations and run simulations of other places in France. While these are examples, the code can adapted to any other scenarios as well:
- Hörl, S. and M. Balac (2020) Reproducible scenarios for agent-based transport simulation: A case study for Paris and Île-de-France, Preprint, IVT, ETH Zurich, Zurich.
- Hörl, S., M. Balac and K.W. Axhausen (2019) Dynamic demand estimation for an AMoD system in Paris, paper presented at the 30th IEEE Intelligent Vehicles Symposium, Paris, June 2019.
- Hörl, S. (2019) An agent-based model of Île-de-France: Overview and first results, presentation at Institut Paris Region, September 2019.
The current version of the pipeline is v1.2.0. You can obtain it by cloning
the v1.2.0 tag of this repository. Alternatively, you can also clone the
develop branch to make use of the latest developments. The version number
will be kept in the develop branch until a new version is officially released.
Note that whenever you create a population with this pipeline, the meta.json
in the output will let you know the exact git commit with which the
population was created.