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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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BikeZ-ETH - A Mass-Cycling Trajectory Dataset from a Controlled Experiment

Authors: Riehl, Kevin; El-Baklish, Shaimaa K.; Ni, Ying-Chuan; Kouvelas, Anastasios; Makridis, Michail;

BikeZ-ETH - A Mass-Cycling Trajectory Dataset from a Controlled Experiment

Abstract

This dataset presents aerial video recordings and trajectory data collected during a controlled mass-cycling experiment during the Cycling Research Board Annual Meeting in Zürich on 06th September 2024 at Hönggerberg Campus of ETH Zürich. 28 cyclists were recorded for a total duration of 30 minutes with a drone from above, and bicycle trajectories were extracted using computer vision and Kalman filtering methodology. As part of the controlled experiment, the number of simultaneous cyclists on the circular track varied between 6 and 22, two lane widths were tested (2.5 and 3.75m), and the flow was disrupted several times to observe acceleration and deacceleration manoeuvres. The folder VIDEOS contains nine video recordings covering a duration of around half an hour (30:07) and 45,175 frames in total, at a framerate of 25 frames per second, and with a resolution of 3840 x 2160 pixels. The videos show more than 30 bicycles riding on the circular track of the Albert Einstein Garage at ETH Zürich Campus Hönggerberg (Zürich, Switzerland) during various experiments. The videos are provided in MP4 format. The folder TRAJECTORIES contains the trajectories for each video, sequence, bicycle, and frame an exact bicycle position. The bicycle trajectories are provided as zipped CSV files, seperated by the comma symbol.Each row consists of 12 columns: (1) Vehicle_ID (2) Frame_ID (3) GlobalTime (in seconds) (4) Cartesian_X (in meter) (5) Cartesian_Y (in meter) (6) Polar_X (in radians) (7) Polar_Y (in meter) (8) v_Length (in meter) (9) v_Width (in meter) (10) v_Vel (in m/s) (11) v_Angle (in radians) (12) v_AngleVel (in rad/s) Source Code Repository The code to extract and process the bicycle trajectories from the videos is available on GitHub: https://github.com/DerKevinRiehl/mass_cycling_experiment Demonstrations https://youtu.be/-UbFwMcpJNk https://youtu.be/b4SxqPf-qpQ https://youtu.be/mCQmYtJ3D8w AcknowledgementsWe would like to thank Catherine Elliot and the other organizers of the Cycling Research Board Annual Meeting (CRB2024), and the initiative Pro Velo Kanton Zurich for promoting the mass-cycling experiment amongst all the experiment participants. Additionally, we would like to thank Judith van den Hoeven for facilitating the coordination with participants, and Veloplan GmbH for the provision of bikes. Moreover, we thank following supporters that facilitated the experiment: Linghang Sun, Kimia Chavoshi, Yifan Zhang, Qishen Zhou. Publications "BikeZ-ETH -- A Longitudinal Trajectory Dataset from an Controlled Mass-Cycling Experiment" (In Submission in "Scientific Data) "The Bicycle Fundamental Diagram: Empirical Insights into Bicycle Flow for Sustainable Urban Mobility" (In Submisison in "Nature Scientific Communications")

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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