Data underlying the master thesis: Predicting cycling risk at intersections with natural cycling data for speed-controlled e-bikes

doi: 10.4121/21736967.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/21736967
Datacite citation style:
Landré, Daniël; Moore, Jason (2022): Data underlying the master thesis: Predicting cycling risk at intersections with natural cycling data for speed-controlled e-bikes. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21736967.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
Delft University of Technology logo
usage stats
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77
downloads
geolocation
Delft, the Netherlands
lat (N): 52.011667
lon (E): 4.359167
view on openstreetmap
time coverage
July 2022 - August 2022
licence
cc-0.png logo CC0

This dataset contains data that was gathered during a master's thesis project. 

During the project, e-bike cycling data was gathered during a natural cycling experiment. Five women and five men aged 20 to 30 years were asked to participate in the experiment. Participants are asked to cycle according to how they would cycle in their daily life.

The experiment consists of two phases. First, participants are instructed to cycle to a random destination in Delft. In the second phase, participants are instructed to cycle two predetermined routes, each time returning to the starting location of the experiment. This results in around 40-45 minutes of cycling data per participant.

The sensor setup of the experiment is tailored toward collecting data that is similar to the data collection capabilities of modern IoT modules carried by e-bikes. 

Data was recorded by various sensors (a high-frequency GNSS antenna, IMU data and power pedals) and correlated against detailed open-access traffic accident data.  

In this dataset, you will find the raw sensor data, processed sensor data, and script used to process the cycling data.

history
  • 2022-12-16 first online, published, posted
publisher
4TU.ResearchData
format
zipped spreadsheet files
organizations
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering (3ME)

DATA

files (1)