Automated Detection of Missing Links in Developed Bicycle Networks

Anastassia Vybornova, Tiago Cunha, Astrid Gühnemann, Michael Szell

Cycling is an effective solution for making urban transport more sustainable. However, bicycle networks are typically developed in a slow, piecewise process that leaves open a large number of gaps, even in well developed cycling cities like Copenhagen. Here, we develop the IPCC procedure (Identify, Prioritize, Cluster, Classify) for finding the most important missing links in developed urban bicycle networks, by analyzing street networks from OpenStreetMap. We apply the IPCC procedure to Copenhagen and report the 105 top priority gaps. For evaluation, we compare these gaps with the city's most recent Cycle Path Prioritization Plan and find considerable overlaps. Our results show how network analysis with minimal data requirements can serve as a cost-efficient support tool for bicycle network planning. The IPCC procedure takes into account the whole city network for consolidating urban bicycle networks and can therefore well complement localized, manual planning processes, providing a data-driven framework for more effective, city-wide decision-making.

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