Motivation
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.
Dataset
The vehicular mobility dataset is mainly based on the data made available by the TAPASCologne project. TAPASCologne is an initiative of 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 street layout of the Cologne urban area is obtained from the OpenStreetMap (OSM) database;
- The microscopic mobility of vehicles is simulated with the Simulation of Urban Mobility (SUMO) software;
- The traffic demand information on the macroscopic traffic flows across the Cologne urban area (i.e., the O/D matrix) is derived through the Travel and Activity PAtterns Simulation (TAPAS) methodology;
- The traffic assignment of the vehicular flows described by the TAPASCologne O/D matrix over the road topology is performed by means of Gawron’s dynamic user assignment algorithm.
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 in a typical working day, and comprises more than 700.000 individual car trips.
Videos
Fast-forward video of the 24-hour vehicular mobility. Each dot represents one car, its speed matching its color (from bright red for standstill vehicles to bright blue for cars traveling at 90 km/h or more).
Publications
The following papers describe the dataset generation process in details:
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S. Uppoor, O. Trullols-Cruces, M. Fiore, J.M. Barcelo-Ordinas,
Generation and Analysis of a Large-scale Urban Vehicular Mobility Dataset,
IEEE Transactions on Mobile Computing, Vol.13, No.5, May 2014 |
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S. Uppoor, M. Fiore,
Large-scale Urban Vehicular Mobility for Networking Research,
IEEE VNC 2011, Amsterdam, The Netherlands, November 2011 |
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S. Uppoor, M. Fiore,
Vehicular mobility in large-scale urban environments,
ACM Mobile Computing and Communications Review, Vol.15, No.4, October 2011 |
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D. Naboulsi, M. Fiore,
Characterizing the Instantaneous Connectivity of Large-scale Urban Vehicular Networks,
IEEE Transactions on Mobile Computing, to appear |
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M. Fiore, A. Nordio, C.-F. Chiasserini,
Driving Factors Toward Accurate Mobile Opportunistic Sensing in Urban Environments,
IEEE Transactions on Mobile Computing, to appear |
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C. Glacet, M. Fiore, M. Gramaglia,
Temporal Connectivity of Vehicular Networks: The Power of Store-Carry-and-Forward,
IEEE VNC 2015, Kyoto, Japan, December 2015 |
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S. Uppoor, M. Fiore,
Characterizing pervasive vehicular access to the cellular RAN infrastructure: an urban case study,
IEEE Transactions on Vehicular Technology, Vol.64, No.6, June 2015 |
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D. Naboulsi, M. Fiore,
On the Instantaneous Topology of a Large-scale Urban Vehicular Network: the Cologne case,
ACM MobiHoc 2013, Bangalore, India, July 2013 |
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S. Uppoor, M. Fiore,
Insights on metropolitan-scale vehicular mobility from a networking perspective,
Invited paper, ACM HotPlanet 2012, Low Wood Bay, UK, June 2012 |
Availability
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.
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.
Download
The SUMO source files that can be used to run a SUMO simulation of the full 24-hour Cologne road traffic are part of the official scenarios available for downdload along with the latest SUMO distribution. You can find them at the SUMO TAPASCologne scenario sourceforge.
The full 24-hour dataset is available as a generic text-format trace 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 compressed file is 7.5 GB in size.
A pruned version of the dataset is available here, in the same generic text-format above. 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.
A file containing the deployment of cellular base stations in Cologne is provided here. The base station location information is in the same format used for the vehicle positions in the generic text-format trace above. It was obtained from public German databases in 2012, and refer to the infrastructure deployed by all operators.
Contacts
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.
