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

Medeiros, Rafael Milani; Bojic, Iva; Jammot-Paillet, Quentin · 2021 · DOAJ

DOI: 10.3390/futuretransp1030037

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Summary

This study investigates the spatiotemporal relationships between bicycle traffic volumes, road crashes, and bikeway infrastructure in Berlin, Germany. Motivated by the surge in urban bicycling during the COVID-19 pandemic and the persistent lack of high-quality, integrated data for planning safe cycling networks, the research aims to validate novel digital data sources against conventional travel surveys. The authors seek to determine how these large-scale datasets can inform future urban bicycling research, planning, and network design by revealing correlations between crash locations, traffic density, and infrastructure types. The methodology utilized three primary digital datasets: 76,292 bicycle trips recorded via the BikeCitizens smartphone application, 38,916 disaggregated bicycling road crashes registered by the Berlin Police over 48 months, and open data from digital bicycle counters at 17 locations. The researchers cleaned the data, filtering out atypical trips and focusing crash analysis on collisions between one bicycle and one motorized vehicle, which accounted for the vast majority of fatalities and severe injuries. Using Geographic Information Systems (GIS), the study mapped these data across 23 spatial units and 1,578 km of bikeways, categorized into six typologies: protected bike paths, two types of dedicated lanes, shared-use lanes for buses or pedestrians, and roads without bikeways. Linear correlation and multivariate regression analyses were performed to assess variations in crashes and volumes over time and space. The results indicate that the spatial distribution of bicycling crashes remained stable over time, with 72% of all crashes, fatalities, and injuries occurring at only 197 road intersections. Most collisions occurred on roads without specific bikeway infrastructure. The study successfully validated the BikeCitizens smartphone data as a reliable proxy for conventional travel surveys, demonstrating that digital sources can provide high-resolution spatiotemporal insights into urban mobility. The integrated analysis revealed distinct patterns in crash density relative to bikeway types, highlighting that infrastructure design significantly influences safety outcomes. The significance of this work lies in its demonstration that ubiquitous digital data sources can effectively complement or substitute traditional, resource-intensive travel surveys for urban bicycling research. By providing a city-wide, high-resolution view of the relationship between traffic volume, crashes, and infrastructure, the findings offer evidence-based guidance for planners. The study underscores the need for integrated data frameworks to design safer, more efficient bikeway networks, addressing the disproportionate risk faced by cyclists and supporting the expansion of sustainable urban mobility.

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• cyclist safety

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• Empirical Findings: crash risk outcomes