Largest multi-city traffic dataset publically available

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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


Standardized dataset

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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


World map

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

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Get the data by signing up, agreeing to our conditions and there you go!

The data will be used only for academic and/or non-commercial purposes.

For any publication that utilizes the UTD19 dataset, authors should include a reference to https://doi.org/10.1038/s41598-019-51539-5.

Include the data source as UTD19 (utd19.ethz.ch) in the acknowledgment section of your publication.
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Center for Interacting Urban Networks

Institute for Transport Planning and Systems