sumo-experiments 1.0.5

The sumo-experiments library implements a python interface for the Simulation of Urban MObility (SUMO) software.

sumo-experiments

The sumo-experiments library implements a python interface for the Simulation of Urban MObility (SUMO) software.

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Table of Contents

1. About The Project
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Contributing
5. License
6. Contact
7. Acknowledgments

About The Project

The sumo-experiments package aims to provide an ergonomic environment for creating and configuring highly reproducible SUMO simulations.

Creating a SUMO network for a simulation is very time-consuming. Infrastructure and flows have to be defined either using the netedit tool, or by manually creating all the numerous XML configuration files. This complexity also makes it difficult to reproduce experiments taken from scientific papers. The sumo-experiments package aims to solve this problem by deploying a set of tools to define SUMO networks, automatically generate configuration files and launch simulations, directly from Python.

For further information, please refer to the jupyter notebooks in the examples folder, which will guide you through the use of the package.

Getting Started

Prerequisites

This package only work with Debian distributions. Also, you must install SUMO. Please refer to the SUMO installation manual.

Installation

1. Get the package from the Python Package Index.

   pip install sumo-experiments
   

2. Check that the $SUMO_HOME environment variable is set. This command must return the value of $SUMO_HOME.

   printenv | grep 'SUMO_HOME'
   

   If the variable is not set, you can add it temporarily with the following command.

   export SUMO_HOME=your_path_to_sumo
   

   To set this variable permanently, write this in the .bashrc file.

Usage

This script is one of the more simple uses of the package. We first instanciate a preset network from preset_networks. This network contains only one intersection, making the junction between two two-way roads, with one lane for each way. Secondly, we instanciate an Experiment with three parameters : - The name of the experiment - A function that defines the infrastructures of the network (nodes, edges, connections, etc) from the preset network - A function that defines the flows of the simulation (vehicle types, density, etc) from the preset network Finally, we run the simulation with the SUMO GUI. We recommand you to use the clean files method to delete all configuration and data files.

from sumo_experiments import Experiment
from sumo_experiments.preset_networks import OneCrossroadNetwork

network = OneCrossroadNetwork()
exp = Experiment('Test', network.generate_infrastructures, network.generate_flows_all_directions)
exp.run(gui=True)
exp.clean_files()

For more examples, please refer to the examples folder

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the LGPL-2.1 License. See LICENSE.txt for more information.

Contact

Jules Bompard - Linkedin - [e-mail]

Project Link: https://github.com/cristal-smac/sumo-experiments

Acknowledgments

• othneildrew for his useful README template.