Introduction
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
40 cities
170 million data rows
23541 detectors
3-5 minute intervals
3.8 years of data
Error-flagged
Standardized dataset
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Access to the dataCities
Augsburg
Basel
Berne
Birmingham
Bolton
Bremen
Bordeaux
Cagliari
Constance
Darmstadt
Essen
Frankfurt
Graz
Groningen
Hamburg
Innsbruck
Kassel
London
Los Angeles
Lucerne
Madrid
Melbourne
Manchester
Marseille
Munich
Paris
Rotterdam
Santander
Speyer
Strasbourg
Stuttgart
Taipei
Tokyo
Toronto
Torino
Toulouse
Utrecht
Vilnius
Wolfsburg
Zurich
Our research
Publications using UTD19 traffic datasets
Understanding traffic capacity of urban networks
Data from 40 cities
Introducing a Re-Sampling Methodology for the Estimation of Empirical Macroscopic Fundamental Diagrams
Data from London and Lucerne
A functional form with a physical meaning for the macroscopic fundamental diagram
Data from Marseille, London, Lucerne, Yokohama, and Zurich.
A case study of Zurich’s two-layered perimeter control
Data from Zurich
Empirical Macroscopic Fundamental Diagrams: New insights from loop detector and floating car data
Data from Zurich
Empirics of multi-modal traffic networks – Using the 3D macroscopic fundamental diagram
Data from Zurich
Capturing network properties with a functional form for the multi-modal macroscopic fundamental diagram
Data 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 data
Data from Zurich
On the modeling of passenger mobility for stochastic bi-modal urban corridors
Data from Zurich
Featured articles and news
Who is writing about the UTD19 traffic data and us?
This is how road networks determine traffic capacity
22/11/2019
Uuring: liikluse sujuvus sõltub neljast tegurist
20/11/2019
How the road network determines traffic capacity
19/11/2019
Empirical Validation of Bimodal MFD Models
4/8/2020
Bi-modal macroscopic traffic dynamics in a single region
01/03/2020
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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
Team
People behind UTD19
