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.
|Number of pages||9|
|Publication status||Published - 2018|
|Event||Transport Research Arena 2018 - Vienna, Austria|
Duration: 16 Apr 2018 → 19 Apr 2018
|Conference||Transport Research Arena 2018|
|Period||16/04/2018 → 19/04/2018|