Our dataset on diluted pedestrian dynamics is available for download at the 4TU datacentrum repository at
The dataset has been employed in our previous publication
 A. Corbetta, C. Lee, R. Benzi, A. Muntean, F. Toschi. Fluctuations around mean walking behaviours in diluted pedestrian flows. Phys. Rev. E. 95, 032316, 2017.
Basic scripts for the usage are available on github at https://github.com/crowdflowTUe/MF_landing_data_analysis
This is a dataset of pedestrian trajectories recorded on a nearly 24/7 schedule in a landing in the Metaforum building at Eindhoven University of Technology. The purpose of the dataset is to enable ensemble analyses of diluted pedestrian motion.
The data acquisition spanned over a year and, overall, we collected about 250.000 trajectories. Via an overhead Microsoft Kinect sensor we first obtained depth imaging, then we employed ad hoc localization algorithms and Particle Tracking Velocimetry to estimate the trajectory of individual heads (cf. ). The current dataset includes 20.000 trajectories from pedestrians walking undisturbed, i.e. in diluted conditions (see Figure). In other words, we considered individuals walking alone in the facility.
The dataset includes 10.000 trajectories of pedestrians crossing the landing entering from the left hand side (file: “left-to-right.ssv”) and 10.000 trajectories of pedestrians entering in the opposite side (file: “right-to-left.ssv”, right-left reference is given according to ).
The trajectories are in the following table format:
Pid Rstep X Y X_SG Y_SG U_SG V_SG
- Pid: unique identifier of a trajectory
- Rstep: identifier of the timestep (starts from zero, the first 5 and last 5 samples are eliminated as typically less precise)
- X,Y: position in Cartesian coordinates (in meters)
- X_SG,Y_SG: position in Cartesian coordinates after Savizky-Golay smoothing (in meters, cf. paper)
- U_SG, V_SG: velocity in Cartesian coordinates after Savizky-Golay smoothing (in meters per second, cf. paper).
To use the dataset please cite  as well as this dataset (DOI: https://doi.org/10.4121/uuid:25289586-4fda-4931-8904-d63efe4aa0b8).