A collection of links to different resources and technologies that might come in handy in a transportation system-modelling context.


Historical and/or real-time traffic data can be obtained through the following providers:

Geodata tools

Traffic data and other relevant data in a transportation modelling context might have important spatial charateristics. Examples are among others:

  • Vehicle trajectory data obtained from a GPS

  • A model of a traffic network. Here the geometry of the network is specified in terms of longtidude and latitude coordinates

In this case different data formats have specifically been developed to accomodate these spatial charateristics. A few number of tools, that make working with geospatial data easier, is given below:

  • JOSM: An editor to work with OpenStreetMap data

  • Geopandas: A python library that extends the pandas library to work with geospatial data types

  • Utm: A python library that can convert between longtitude and latitude coordinates and coordinates given in the Universal Transverse Mercator (UTM) coordinate system

Mapping Platforms

Several mapping platforms exist for creating interactive maps, which can be explored through a browser or a mobile application. Many of the mapping platforms, listed below, provide additional features for analysis of geospatial data, vehicle routing, travel time calculation based on predictive traffic information, etc. These platforms are usually free to use up to a certian number of Application Programming Interface (API) calls.

Links to interesting websites and projects, that are relevant in a transportation modelling context:

  • DataFromSky: Monitoring and analysis of traffic at intersections by the use of aerial video (Demo)

  • Gisagents: A website that is concerned with the latest advances in the fields of Geographical Information Systems (GIS) and Agent-based modelling (ABM)

  • TensorTraffic: A TensorFlow-based tool for predicting the outcome of a traffic simulation.

  • Visualization of O-D matrices: Agent-based visualization of origin-destination matrices

Note: This post will be extented over time. Last edited: 09-08-2018.