The 'Safety in Numbers' (SiN) effect proposes that when the volume of cycling traffic increases, the number of crashes increases less (relative to the cycling volume). A recent meta-analysis supported the general idea of a SiN effect, but also highlighted the heterogeneity of its strength, also see). The authors of this meta-study conclude that the SiN effect is strenger at the macro-level than at the micro-level, but bears no clear relationship to the quality of the cycling infrastructure. The mechanisms producing the SiN effect are still unknown. Possible explanations are (i) that safer street regulations and designs are more likely to ex.ist in societies with more wallcing and bicycling; (ii) changes in the behavior of people walking or bicycling; or (iii) changes in behavior of drivers. However, all of these explanations have their shortcomings. Additionally, some authors have argued that an increase in the number of crashes cannot be ruled out due to the increasing numbe:r of inexpe:rienced or particularly risk-taking cyclists. The:re appears to be little research on the question whether and how the SiN effect may be linked to specific road types featuring different combinations of speed zones and cycling infrastructures. Furthermore, the base rate of cyclists (i.e. the cycling volume) is a highly relevant factor when investigating the distribution of crashes throughout different road types [6]. In our research, we thus use a GIS-based approach aimed at testing the relation between the cycling volume and the number of crashes involving cyclists for roads featuring different speed zones and cycling infrastructures.