Several cities and national authorities across the globe publish records on road accidents and crashes. This data is vital for road safety analysis, enabling researchers to develop models to understand how different factors impact the frequency and severity of accidents. However, researchers studying cycling safety face additional challenges as datasets containing solely cycling accidents are scarce, usually in the country's original language, may contain errors, among others. We publish CYCLANDS, a curated collection of 30 datasets on cycling crashes to lower the barrier in objective cycling research comprising nearly 1.6M cycling accidents. All observations include the severity of the accident. This collection fosters the worldwide study of cycling safety by providing a testbed for researchers to develop tools and models for cycling safety analysis, ultimately improving the safety of those who cycle.
Please find this article here.
- Use the code in Dataset Curation to curate each dataset.
Check out our website to easily explore the data here.
Our code is under MIT license.
If you find this project useful for your research, please use the following BibTeX entry.
@article{costa2022cyclands,
title={CYCLANDS: Cycling geo-located accidents, their details and severities},
author={Costa, Miguel and Marques, Manuel and Roque, Carlos and Moura, Filipe},
journal={Scientific data},
volume={9},
number={1},
pages={237},
year={2022},
publisher={Nature Publishing Group UK London}
}