Identifying and classifying gaps in the bicycle network of Copenhagen

Identifying and classifying gaps in the bicycle network of Copenhagen

Faculty of Science, University of Copenhagen 2021

Cycling is a promising solution for making urban transport systems more sustainable. The planning of bicycle networks can be supported with computational concepts from network theory applied to massive crowdsourced data sets, allowing for data-driven and potentially more efficient decision-making. However, there is no consolidated methodology in the application of network analysis to bicycle infrastructure. This study contributes to the consolidation of computational methods for bicycle network planning by tackling the specific task of identifying gaps in a bicycle network. We show how the detection and prioritization of gaps in an urban bicycle network can be automatized by topological network analysis of open source data from OpenStreetMap (OSM). To this end, we develop a four-step procedure (identify, cluster, classify, and prioritize) for finding the most important network gaps based on topological network metrics. We apply our procedure to Copenhagen, Denmark, and report the 101 top priority gaps found in the network. To evaluate our results, we compare our findings with the current Cycle Path Prioritization Plan of the Municipality of Copenhagen, and find considerable overlaps with citizen survey data. Our results show how network analysis with minimum data requirements can serve as a powerful and cost-efficient tool for bicycle network planning. Our procedure takes into account the entire urban bicycle network and can therefore meaningfully complement localized, manual planning processes for effectively consolidating dense urban bicycle networks.

bicycle network planning; transport network analysis; sustainable mobility; MASTERPROGRAMMETHESIS

Open access content. Open access content

116 pages
application/pdf
English

DAV oai:pure.atira.dk:studentproject/65fb2b76-186d-4afe-9f18-4ef997106be6
1285232728

UNIV OF COPENHAGEN
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