Giter Site home page Giter Site logo

eqasim-org / sao_paulo Goto Github PK

View Code? Open in Web Editor NEW
14.0 2.0 4.0 46.13 MB

An open synthetic population of Sao Paulo Metropolitan region for agent-based transport simulation

License: GNU General Public License v2.0

Python 5.45% Jupyter Notebook 94.55%
transportation scenario agent-based sao-paulo brasil

sao_paulo's Introduction

An open synthetic population of Sao Paulo Metropolitan Region

Via Sao-Paulo

This repository contains the code to create an open data synthetic population of the Sao Paulo Metropolitan region. It can also be used to create scenarios for other regions in Brasil, given that an appropriate household travel survey is available.

Scenario download

In case you wish to use the generated synthetic travel demand or agent-based scenario directly, they are available here:

To run the simulation directly with the provided scenario you need to use the eqasim environment. The main class requiring only the config file as an input is available here.

The scenario is created using this repository with the version 1.1.

Main reference

The main research reference for the general pipeline methodology 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.

The main research reference for the Sao Paulo synthetic population is:

Sallard, A., M. Balac and S. Hörl (2021) An open data-driven approach for travel demand synthesis: an application to São Paulo, Regional Studies, Regional Science, 8(1), 371-386.

What is this?

This repository contains the code to create an open data synthetic population of the Sao Paulo Metropolitan region. 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 Sao Paulo 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.

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!

Publications

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.