Spatiotemporal Variation in Bicycle Road Crashes and Traffic Volume in Berlin: Implications for Future Research, Planning, and Network Design

Abstract

Urban bicycling has been largely marginalized for decades in the global north and south. Despite a renaissance over the last two decades in academic research, political discourse, sustainability activism, and planning, cities often struggle with data quality and quantity. Digitalization has led to more and better data sources, but they still must be validated and compared with findings from conventional travel surveys. With the COVID-19 pandemic, bicycling and associated road facilities expanded, as did road crashes involving bicycles. This study utilized tens of thousands of datapoints sourced by public institutions and digital devices belonging to private companies that have spread across Berlin over the last ten years and are currently ubiquitous. What does an integrated analysis of data from these novel sources reveal for urban bicycling research, planning, and network design? We explored and visualized the relationships and spatiotemporal variations in (i) bicycling volumes and (ii) crashes, unveiling the (iii) distribution of and correlation between datasets and the city’s bikeway network at an unprecedented threshold. The findings can be useful for special interest groups and to guide future urban bicycling research, planning, and network design.