Pedelecs (pedal electric cycles) have become increasingly popular in recent years. This increase may trigger many positive effects, but unfortunately it also results in an increase in accidents, especially single accidents, involving these vehicles. This investigation analyses 1738 free text descriptions of pedelec single accidents written by police officers on site. The accidents occurred in 2016 and 2017 in 14 federal German states. The aim is to evaluate whether pedelec single accidents have specific causes that have not yet been recorded in the official accident statistics. Results show that most cases can be assigned to categories addressing the user (60 %) or the road design (54 %, accidents can be assigned to several categories). With this dataset it is also possible to analyse the severity of injuries using ordered probit analysis. Of the nine categories where severe injuries are expected, most address the user. In addition, serious injuries are expected when problems are encountered on downhill slopes or involve technical faults. An additional ordered probit analysis with a second dataset, based on different sources but using the same categorisation, supports these results.

近年来，Pedelecs（脚踏电动自行车）变得越来越流行。这种增加可能会引发许多积极影响，但不幸的是，这还会导致涉及这些车辆的事故（尤其是单次事故）增加。这项调查分析了由警察在现场写的1738辆单脚电动自行车事故的免费文字描述。事故于2016年和2017年在德国的14个联邦州发生。目的是评估单车事故是否具有尚未在官方事故统计中记录的特定原因。结果表明，大多数情况可以分配给解决用户的类别（60％）或道路设计（54％，事故可以分配给几个类别）。利用该数据集，还可以使用有序概率分析来分析伤害的严重程度。在预计会造成严重伤害的九种类别中，大多数针对用户。此外，当在下坡上遇到问题或涉及技术故障时，预计会造成严重的人身伤害。基于不同的来源但使用相同的分类，使用第二个数据集进行的另外的有序概率分析也支持这些结果。