Transportation Networks for Research
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README.md

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.

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 Transportation Networks for Research 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.

How to Cite

Transportation Networks for Research Core Team. Transportation Networks for Research. https://github.com/bstabler/TransportationNetworks. Accessed Month, Day, Year.

Core Team

This repository is maintained by the Transportation Networks for Research Core Team. The current members are:

This effort is also associated with the TRB Network Modeling Committee. If you are interested in contributing in a more significant role, please get in touch. 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 ; …..

Summary of Networks

Network Zones Links Nodes
Anaheim 38 914 416
Austin 7388 18961 7388
Barcelona 110 2522 1020
Berlin-Center 865 28376 12981
Berlin-Friedrichshain 23 523 224
Berlin-Mitte-Center 36 871 398
Berlin-Mitte-Prenzlauerberg-Friedrichshain-Center 98 2184 975
Berlin-Prenzlauerberg-Center 38 749 352
Berlin-Tiergarten 26 766 361
Birmingham-England 898 33937 14639
Braess-Example 2 5 4
Chicago-Sketch 387 2950 933
Eastern-Massachusetts 74 258 74
Hessen-Asymmetric 245 6674 4660
Philadelphia 1525 40003 13389
SiouxFalls 24 76 24
Terrassa-Asymmetric 55 3264 1609
Winnipeg 147 2836 1052
Winnipeg-Asymmetric 154 2535 1057
chicago-regional 1790 39018 12982

Other Related Projects

  • TRB Network Modeling Committee
  • Highway Assignment
    • 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.
    • 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
    • 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
    • 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.
    • DTALite-S - Simplified Version of DTALite for Education and Research
    • NeXTA open-source GUI for visualizing static/dynamic traffic assignment results
  • Transit Assignment
    • Fast-Trips - open source dynamic transit assignment software, data standards, and research project
  • Data Schemas
    • AMS Data Hub is an FHWA research project to develop a prototype data hub and data schema for transportation simulation models
    • GTFS-PLUS - GTFS-based data transit network data standard suitable for dynamic transit modeling
    • Open matrix - Open matrix standard for binary matrix data management that is supported by the major commercial travel demand modeling packages and includes code for R, Python, Java, C#, and C++.