Abstract

The National accident database is often used as basis when designing and prioritizing safety initiatives for cyclists.
Due to the very low reporting rate this is not optimal. The purpose of this study is to get a better understanding of
factors influencing the occurrence of cyclist accidents with a particular focus on the influence of the condition of
the road. The study is based on data on cyclist injuries reported to the hospital and merged with road data, including
information on road condition and existence of bicycle lane. The data is analyzed using a Latent Class Clustering
approach for pattern recognition. The analysis uncovers patterns of road maintenance and cyclists accidents and
reveals 11 clusters. The results identify the road condition as a significant factor for many of the accidents,
especially for accidents involving less experienced cyclists. In addition, the analysis confirms that the use of
medical records together with road maintenance data leads to new insight of the occurrence of bicycle accidents,
which is relevant for the prioritization of preventive efforts.

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Original document

The different versions of the original document can be found in:

https://zenodo.org/record/1456589 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
http://orbit.dtu.dk/ws/files/163241335/Contribution_10620_fullpaper.pdf,
https://zenodo.org/record/1456589
http://dx.doi.org/10.5281/zenodo.1456588 under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
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DOIS: 10.5281/zenodo.1456589 10.5281/zenodo.1456588

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Published on 01/01/2018

Volume 2018, 2018
DOI: 10.5281/zenodo.1456589
Licence: Other

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