Cycling Research Board Annual Meeting

Contemporary bicycle network planning is largely an ad hoc process based on little empirical evidence, sometimes outsourced to for-profit consultancies working with opaque methods. Algorithms can be of great assistance in turning bicycle network planning into a more empirical and systematic process. When such algorithms are created open-source, and developed in a user-friendly way, they become particularly effective and reproducible for planners, even allowing for citizen science and use by sustainable mobility advocates. Therefore, to sustainably boost urban cycling, we urgently need user-friendly, open-source planning software. Here, we document our ongoing work turning 10 raw bicycle network algorithms — developed in the last 6 years at our research group — into BikeNetKit, an open-source, reproducible, packaged software suite. It is also not enough to provide functioning software, but the benefits of such a software must be well accessible, also to policy makers and the general public. For a few of the past algorithms we have already developed accompanying interactive data visualization platforms, most importantly www.growbike.net and www.fixbike.net. However, several of the algorithms are missing such visualizations. To develop such visualizations and to embed them via a consistent web experience, we hired a web developer / visualization expert. We expect the outcome of this task to further close the gap between sustainable planning research and policy making. BikeNetKit is targeted at, and developed with the input of, urban planners and policy-makers. Using the example of bicycle network planning, we share our broader reflections on the research-to-policy pipeline with the cycling research community.