Transportation Networks

Transportation Networks is a networks repository for transportation research.

If you are developing algorithms in this field, you probably asked yourself more than once: where can I get good data? The purpose of this site is to provide an answer for this question! This site currently contains several examples for the traffic assignment problem. Suggestions and additional data are always welcome.

Many of these networks are for studying the Traffic Assignment Problem, which is one of the most basic problems in transportation research. Theoretical background can be found in “The Traffic Assignment Problem – Models and Methods” by Michael Patriksson, VSP 1994, as well as in many other references.

This repository is an update to Dr. Hillel Bar-Gera's TNTP. As of May 1, 2016, data updates will be made only here, and not in the original website.

How To Download Networks

Each individual network and related files is stored in a separate folder. There are a number of ways to download the networks and related files:

• Click on a file, click view as Raw, and then save the file
• Clone the repository to your computer using the repository's clone URL. This is done with a Git tool such as TortoiseGit. Cloning will download the entire repository to your computer.

How To Add Networks

There are two ways to add a network:

• Fork the repo
  • Create a GitHub account if needed
  • Fork (copy) the repo to your account
  • Make changes such as adding a new folder and committing your data
  • Issue a pull request for us to review the changes and to merge your changes into the master
• Create an issue, which will notify us. We will then reply to coordinate adding your network to the site.

Make sure to create a README in Markdown for your addition as well. Take a look at some of the existing README files in the existing network folders to see what is expected.

If you are interested in contributing in a more significant role, please get in touch with the team. Thanks!

Formats

Any documented text-based format is acceptable. Please include a README.MD that describes the files, conventions, fields names, etc. It is best to use formats that can be easily read in with technologies like R, Python, etc. Many of the datasets on TransportationNetworks are in TNTP format.

TNTP Data format

TNTP is tab delimited text files, with each row terminated by a semicolon. The files have the following format:

• First lines are metadata; each item has a description. An important one is the <FIRST THRU NODE>. In the some networks (like Sioux-Falls) it is equal to 1, indicating that traffic can move through all nodes, including zones. In other networks when traffic is not allow to go through zones, the zones are numbered 1 to n and the <FIRST THRU NODE> is set to n+1.
• Comment lines start with ‘~’.
• Network files – one line per link; links are directional, going from “init node” to “term node”.
  • Link travel time = free flow time * ( 1 + B * (flow/capacity)^Power ).
  • Link generalized cost = Link travel time + toll_factor * toll + distance_factor * distance
  • The network files also contain a "speed" value for each link. In some cases the "speed" values are consistent with the free flow times, in other cases they represent posted speed limits, and in some cases there is no clear knowledge about their meaning. All of the results reported below are based only on free flow travel times as described by the functions above, and do not use the speed values.
  • The standard order of the fields in the network files is:
    • Init node
    • Term node
    • Capacity
    • Length
    • Free Flow Time
    • B
    • Power
    • Speed limit
    • Toll
    • Link Type
• Trip tables – An Origin label and then Origin node number, followed by Destination node numders and OD flow

Origin origin#
destination# , OD flow ; …..

License

All data is currented donated. Data sets are for academic research purposes only. Users are users are fully responsible for any results or conclusions obtained by using these data sets. Users must indicate the source of any dataset they are using in any publication that relies on any of the datasets provided in this web site. The TransportationNetworks team is not responsible for the content of the data sets. Agencies, organizations, institutions and individuals acknowledged in this web site for their contribution to the datasets are not responsible for the content or the correctness of the datasets.

Other Related Projects

• InverseVIsTraffic is an open-source repository that implements some inverse Variational Inequality (VI) formulations proposed for both single-class and multi-class transportation networks. The package also implements algorithms to evaluate the Price of Anarchy in real road networks. Currently, the package is maintained by Jing Zhang.
• TRB Network Modeling Committee
• Frank-Wolfe algorithm that demonstrates how to read these data formats and runs a FW assignment. The header file "stdafx.h" is for Microsoft Visual C (MSVC) compiler. On Unix and other compilers it can be simply omitted.
• Origin-Based Assignment (OBA) algorithm
• NeXTA open-source GUI for visualizing static/dynamic traffic assignment results
• seSue is an open source tool to aid research on static path-based Stochastic User Equilibrium (SUE) models. It is designed to carry out experiments to analyze the effects of (1) different path-based SUE models associated with different underlying discrete choice models (as well as hybrid models), and (2) different route choice set generation algorithms on the route choice probabilities and equilibrium link flows. For additional information, contact [Ugur Arikan] ([email protected])
• TrafficAssignment.jl is an open-source, Julia package that implements some traffic assignment algorithms. It also loads the transportation network test problem data in vector/matrix forms. The packages is maintained by Changhyun Kwon.
• AMS Data Hub is an FHWA research project to develop a prototype data hub and data schema for transportation simulation models