Understanding the dynamics of vehicles is a major issue in smart cities evolution. Impacts are
preponderant in user guidance, fuel consumption, pollution, but also in instrumentation efforts
to deploy the infrastructures of communication. Most
concentrate on macro-mobility with centralized decisions and global optimizations for whole cities.
With the great development of autonomous cars
systems, micro-mobility is again of special importance for opportunistic data dissemination and
local decisions - for instance when arriving at traffic lights or when vehicles meet.
We believe in the strong integration of the two approaches - hybrid decentralized ITS.
Simulation tools are widely used to evaluate assumption correctness and performances of optimization algorithms. Several macroscopic vehicular mobility trace exist, but few detailed ones at the microscopic level. Most of macro traces integrate simplistic models for intersections and roundabout, while the complexity of this fine-grained mobility can greatly affect the global optimization. For that purpose, we propose a dataset describing a complex roundabout in Creteil, France.
#Car #Bus #Traffic #Light
The vehicular mobility dataset is mainly based on the real data collected by the General Departmental Council of Val de Marne (94) in France. The General Departmental Council of Val de Marne is a regional agency in charge - amongst other activities - of the transportation systems.
Different simulations tools and models are brought together to characterize and synthesize this trace:
#Flux #Sharing #Reproducibility
Microscopic vehicular mobility trace of Europarc roundabout, Creteil, France by Marie-Ange Lèbre, Frédéric Le Mouël is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The trace contains in each line the time (1-second granularity), the vehicle slope (not used), the
vehicle lane, the vehicle angle, the vehicle type (vehicle or bus), the vehicle position, the vehicle
coordinates on the two-dimensional plane (x and y coordinates in meters), the vehicle speed (in meters
per second), and the vehicle id.
The trace is in CSV format, zipped.
Reference to this dataset can be made as follows - to the publication:
Marie-Ange Lèbre, Frédéric Le Mouël, Eric Ménard. "On the Importance of Real Data for Microscopic Urban Vehicular Mobility Trace". In Proceedings of the 14th International Conference on ITS Telecommunications (ITST'2015), Copenhagen, Denmark, December 2015.
or to the core data itself:
Marie-Ange Lèbre, Frédéric Le Mouël, Eric Ménard. "Microscopic vehicular mobility trace of Europarc roundabout, Creteil, France", April, 2015.
M.-A. Lèbre, F. Le Mouël, and E. Ménard. "Resilient, Decentralized V2V Online Stop-free Strategy in a Complex Roundabout". In Proceedings of the IEEE 83rd Vehicular Technology Conference (VTC'2016-Spring), Nanjing, China, May 2016.
M.-A. Lèbre, F. Le Mouël, and E. Ménard, A. Garnault, B. Bradaï, and V. Picron. "Real scenario and simulations on GLOSA traffic light system for reduced CO2 emissions, waiting time and travel time". In Proceedings of the 22th Intelligent Transport Systems and Services World Congress (ITS World Congress'2015), Bordeaux, France, October 2015.
#JointWork #University #Industry #Regional #Agencies
This research results from a joint work between an academic partner - the University of Lyon, INSA Lyon, INRIA CITI Lab, Dynamid team - and an industrial partner - the Valeo Group. Many thanks to the General Departmental Council of Val de Marne for their support to the real data collecting.