Corbetta, Alessandro; Toschi, Federico (2017): Crowdflow – diluted pedestrian dynamics in the Metaforum building of Eindhoven University of Technology. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:25289586-4fda-4931-8904-d63efe4aa0b8

Dataset

• Human Geography

Active matter, Diluted pedestrian motion, Pedestrian dynamics, Pedestrian tracking, Statistical physics

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2013-06/2015-04

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by Alessandro Corbetta , Federico Toschi

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 data acquisition spanned over a year and, overall, about 250.000 trajectories have been collected. Depth imaging data has been first obtained via an overhead Microsoft Kinect sensor, then ad hoc localization algorithms and PTV-like tracking have been employed to estimate the trajectory of individual heads (cf. publication). The current dataset includes 20.000 trajectories from pedestrians walking undisturbed i.e. in diluted conditions (individuals are walking alone in the facility). There are 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 publication linked). The purpose of the dataset is to enable ensemble analyses of diluted pedestrian motion. 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).

• 2017-10-02 first online, published, posted

TU Eindhoven

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• http://crowdflow.phys.tue.nl/
• https://doi.org/10.1103/PhysRevE.95.032316
• https://github.com/crowdflowTUe/MF_landing_data_analysis

Eindhoven University of Technology, Department of Applied Physics, Turbulence and Vortex Dynamics;
Eindhoven University of Technology, Department of Mathematics and Computer Science, Centre for Analysis, Scientific computing and Applications