Simulation is the tool of choice for the large-scale performance evaluation of upcoming telecommunication networking paradigms that involve users aboard vehicles, such as next-generation cellular networks for vehicular access, pure vehicular ad hoc networks, and opportunistic disruption-tolerant networks.

The single most distinguishing feature of vehicular network simulation lies in the mobility of users, resulting from complex macroscopic and microscopic dynamics.

Today’s challenge lies in generating traffic traces that (i) compass very large urban areas, i.e., whole cities including their surroundings, and (ii) are realistic also from a macroscopic point of view, i.e., that faithfully mimic large traffic flows across a metropolitan area.


The vehicular mobility dataset is mainly based on the data made available by the TAPASCologne project. TAPASCologne is an initiative by the Institute of Transportation Systems at the German Aerospace Center (ITS-DLR), aimed at reproducing, with the highest level of realism possible, car traffic in the greater urban area of the city of Cologne, in Germany.

To that end, different state-of-art data sources and simulation tools are brought together, so to cover all of the specific aspects required for a proper characterization of vehicular traffic:

The resulting synthetic trace of the car traffic in a the city of Cologne covers a region of 400 square kilometers for a period of 24 hours, comprising more than 700.000 individual car trips.


Fast-forward video of the 24-hour vehicular mobility. Each dot represents one car, its speed matching its color (from bright red for still vehicles to bright blue for cars traveling at 90 km/h or more).


More information about the dataset can be found in the following papers:


The data is available under the Creative Commons licence. You must tell where the data is from, it is not to be used for commercial purposes, as soon as you use it we want to be informed about it.

We provide a 2-hour subset of the dataset for download, see section Download below. Our agreement with ITS-DLR does not allow us distributing the full 24-hour dataset. If you are interested in the complete mobility data, please contact ITS-DLR directly, through the SUMO mailing list.

If you employ the mobility dataset for your research, please acknowledge our work by referencing one or more of the papers listed above. You are free to pick the paper(s) that you feel are the most relevant to your study.


A 2-hour mobility trace (6am to 8am) is available for download below, in different formats. For information on the full 24-hour dataset, see section Availability above.

A generic-format trace is available here. The trace format is generic in the sense that it is not thought for use with a specific network simulator). More precisely, each line of the trace contains the time (with 1-second granularity), the vehicle identifier, its position on the two-dimensional plane (x and y coordinates in meters) and its speed (im meters per second). The trace is compressed with xz in order to minimize the download size, however the data still needs 1.2 GB of free disk space approximately.

A ns-2 trace is available here. This trace can be fed to the ns-2 simulator to generate the movement of vehicular nodes during the simulation. Please note that the download size is 1.6 GB approximately.

The source files used for the SUMO simulation are available for download at the official TAPASCologne website.

A generic-format trace of the Pruned mobility dataset is available here. The Pruned dataset is a simplified version of the original road traffic dataset. It is generated by considering the same travel demand and traffic assignment of the original Cologne dataset. However, it only includes major roads in the city and employs a simpler microscopic mobility model, i.e., the Constant Speed Motion with Pauses. The Pruned dataset has been used in some of our papers above in order to demonstrate the impact of unrealistic mobility models on the network of communication-enabled vehicles.


Sandesh Uppoor is a postdoctoral fellow at UPMC. Prior to that, he was a PhD student at INSA Lyon and a member of the Alcatel Lucent Bell Labs - Inria common lab.
Diala Naboulsi is a postdoctoral fellow at Concordia University. Prior to that, she was a PhD student at INSA Lyon and a member of the Inria UrbaNet team.
Marco Fiore is a researcher at CNR-IEIIT and a collaborator of the Inria UrbaNet team.