Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001, Lisboa, Portugal.
Institute for Systems and Robotics, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1, 1049-001, Lisboa, Portugal.
Sci Data. 2022 May 26;9(1):237. doi: 10.1038/s41597-022-01333-2.
Several cities and national authorities across the globe publish records on road accidents and crashes. This data is vital for road safety analysis, enabling researchers to develop models to understand how different factors impact the frequency and severity of accidents. However, researchers studying cycling safety face additional challenges as datasets containing solely cycling accidents are scarce, may contain errors, among others. Thus, we publish CYCLANDS: CYCling geo-Located AccideNts, their Details and Severities. CYCLANDS is a curated collection of 30 datasets on cycling crashes to lower the barrier in objective cycling research comprising nearly 1.6 M cycling accidents. All observations include the severity and location of the accident. This collection fosters the worldwide study of cycling safety by providing a testbed for researchers to develop tools and models for cycling safety analysis, ultimately improving the safety of those who cycle.
全球有几个城市和国家当局发布道路事故和碰撞记录。这些数据对于道路安全分析至关重要,使研究人员能够开发模型来了解不同因素如何影响事故的频率和严重程度。然而,研究自行车安全的研究人员面临着额外的挑战,因为仅包含自行车事故的数据集很少,可能包含错误等。因此,我们发布了 CYCLANDS:CycLing 地理位置事故、其细节和严重程度。CYCLANDS 是一个经过精心整理的包含 30 个自行车碰撞数据集的集合,旨在降低客观自行车研究的门槛,其中包含近 160 万起自行车事故。所有观察结果都包括事故的严重程度和位置。该数据集通过为研究人员提供一个用于开发自行车安全分析工具和模型的测试平台,促进了全球范围内的自行车安全研究,最终提高了骑自行车者的安全性。