In July 2020, Mr. Joachim Landtmeters, MSc student from KU Leuven, successfully conducted the defence of his thesis titled “Analyzing mixed urban traffic by linking large scale trajectory dataset to underlying network”. Mr. Landtmeters had the opportunity to develop a tool to easily get traffic characteristics at any location in the network through a map-matching approach and to analyze multimodal urban traffic.

The designed framework utilized the pNEUMA dataset to extract a road network with all needed attributes. Then it matches the trajectories to the underlying network and by placing virtual loops anywhere in the network, one can directly measure the traffic characteristics.

The challenges of integrating existing map-matching algorithms to this unique dataset are thoroughly discussed and different ways to tackle all identified issues were developed.

The specific work was presented in the MFTS2020 conference and as the pNEUMA dataset is part of an open science initiative, the code of the specific work is openly shared and can be found online here.