A unique dataset
UTD19 is a large-scale traffic dataset from over 23541 stationary detectors on urban roads in 40 cities worldwide making it the largest multi-city traffic dataset publically available.
The Institute for Transport Planning and Systems ETH Zurich collected the data in a research campaign from 2017-2019. The data mainly consists of measurements from loop detectors, which record vehicle flow and occupancy (or speed) in relatively small aggregation interval, typically 3-5min. The location of all detectors and the associated roads have been geo-coded in WGS84 coordinates making map matching as easy as possible. Its use is open to researchers from all over the world.
UTD19 at a glance
Stats on our traffic dataset
4.9 billion detected vehicles
170 million data rows
3-5 minute intervals
3.8 years of data
The UTD19 traffic data is for free. You only have to sign up and agree with our conditions, and you are all set.Access to the data
Publications using UTD19 traffic datasets
Understanding traffic capacity of urban networksData from 40 cities
Introducing a Re-Sampling Methodology for the Estimation of Empirical Macroscopic Fundamental DiagramsData from London and Lucerne
A functional form with a physical meaning for the macroscopic fundamental diagramData from Marseille, London, Lucerne, Yokohama, and Zurich.
A case study of Zurich’s two-layered perimeter controlData from Zurich
Empirical Macroscopic Fundamental Diagrams: New insights from loop detector and floating car dataData from Zurich
Empirics of multi-modal traffic networks – Using the 3D macroscopic fundamental diagramData from Zurich
Capturing network properties with a functional form for the multi-modal macroscopic fundamental diagramData from London and Zurich
A multimodal network interaction model for the macroscopic fundamental diagram (MFD)Data from Zurich and London
Approximative network partitioning for MFDs from stationary sensor dataData from Zurich
On the modeling of passenger mobility for stochastic bi-modal urban corridorsData from Zurich
Featured articles and news
Who is writing about the UTD19 traffic data and us?
This is how road networks determine traffic capacity22/11/2019
Uuring: liikluse sujuvus sõltub neljast tegurist20/11/2019
How the road network determines traffic capacity19/11/2019
Empirical Validation of Bimodal MFD Models4/8/2020
Bi-modal macroscopic traffic dynamics in a single region01/03/2020
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Loder, A., L. Ambühl, M. Menendez and K.W. Axhausen (2019) Understanding traffic capacity of urban networks, Scientific Reports, 9 (1) 16283. https://doi.org/10.1038/s41598-019-51539-5