Visualization of Travel Times in a Road Network
The Smart Mobility Lab at KTH is in cooperation with several companies in the transport industry, researching optimization of transport of both goods and people. Companies in the transport industry track their vehicles as they move through the road networks; this creates a lot of data that can be valuable in determining, for example, the current flow rates at different parts of the road network. Given such historical data, predictions can be made for how the network will behave at points in the future, the knowledge of which can be used to further optimize path planning of vehicles.
The aim of this project was to create a toolkit for visualizing existing data gathered by companies in the transport industry (or even simulated data) for helping researchers to be able to identify interesting points of a road network and drawing conclusions in a quick manner.
The result of the project was a Python library that communicates with a PostgreSQL database with PostGIS extensions. Using only open-source libraries, the library written in this project is able to fetch data about a road network's nodes and edges (junctions and roads) along with their travel times, and overlay the data on a Google Earth map (in the form of .kml files). The library is also able to calculate shortest paths in the road network at a given time.
The library was mainly designed to work on the city size-level, and to only render overlays for Google Earth, but it can relatively easily be extended to work on the country (or even continent) size-levels, as well as creating overlays for other map standards.
Ari Hauksson