With the focus that cities around the world have put on sustainable transportation during the past few years, biking has become one of the foci for local governments globally. Cities all over the world invest in biking infrastructure, including bike lanes, bike parking racks, shared (dockless) bike systems etc. However, one of the critical factors in converting city-dwellers to (regular) bike users/commuters is safety. In this work, we utilize bike accident data from different cities to model the biking safety based on street-level (geographical and infrastructural) features. Our evaluations indicate that our model provides well-calibrated probabilities that accurately capture the risk of a biking accident. We further perform cross-city comparisons in order to explore whether there are universal features that relate to cycling safety. Finally, we discuss and showcase how our model can be utilized to explore “what-if” scenarios and facilitate policy decision making.

在过去几年中，由于世界各地的城市都将重点放在可持续交通上，骑自行车已成为全球地方政府关注的焦点之一。全世界的城市都在对自行车基础设施进行投资，包括自行车道，自行车停车架，共享（无坞）自行车系统等。但是，将城市居民转换为（常规）自行车用户/通勤者的关键因素之一是安全性。在这项工作中，我们利用来自不同城市的自行车事故数据来基于街道（地理和基础设施）特征对自行车安全性进行建模。我们的评估表明，我们的模型提供了经过良好校准的概率，可以准确地捕获骑车事故的风险。我们将进一步进行跨城市比较，以探索是否存在与骑行安全相关的通用功能。最后，