Data collection & processing
Drone-based observations
High-resolution cycling trajectories were collected via drone-based observations in collaboration with MobiLysis at thirteen locations in the city of Zurich, Switzerland. The data were filtered and transformed into lane-based coordinates to facilitate further analysis. In addition, we reconstructed the trajectories into animations, establishing a data-driven digital twin of the observed vehicle and bicycle movements.
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Map of the City of Zurich
Location details
Maps
Experiment type
Controlled
Description
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, separated by the comma symbol.
The first six videos (3,4,5,7,8,9) have the lane width of 2.5 m, while the last three videos (10,11,12) have the lane width of 3.75 m.
Data format
(1) Vehicle_ID (2) Frame_ID (3) GlobalTime [second] (4) Cartesian_X [meter] (5) Cartesian_Y [meter] (6) Polar_X [radian] (7) Polar_Y [meter] (8) v_Length [meter] (9) v_Width [meter] (10) v_Vel [m/s] (11) v_Angle [radian] (12) v_AngleVel [rad/s]
