Introduction

Sustrans and the Department for Transport commissioned ITS Leeds to develop the Rapid Cycleway Prioritisation Tool to help identifying promising locations for new cycleways in England. The immediate purpose of this project is to inform bids for Tranche 2 of the Emergency Active Travel Fund, particularly for authorities which have not yet developed Local Cycling and Walking Investment Plans (LCWIP). Tranche 2 will fund temporary or permanent infrastructure schemes aimed at increasing active travel and helping to shift people away from public transport given capacity constraints imposed by social distancing.

For each combined and local authority, the tool identifies existing cycleways, promising locations for new cycleways on roads with spare space (‘top ranked new cycleways’) and what a cohesive cycling network might look like in the longer-term.

How does the tool identify ‘top ranked new cycleways’?

The tool identifies priority locations for new cycleways, ranking roads by their ‘cycling potential’ estimated using the Propensity to Cycle Tool (PCT). This represents the estimated number of cycling trips along this road travelling to or from work or school assuming the Government’s aim to double cycling by 2025 is met.

The ‘top ranked new cycleways’ represents the roads with the highest cycling potential which also have spare space; that is, are either wide or have two or more road lanes in one direction. We have restricted the analysis to focusing on roads with spare lanes since these have the capacity to accommodate new cycleways whilst maintaining two-way traffic. New cycleways on these routes may therefore be faster to deliver than those requiring roads to be closed to traffic or introducing one-way systems. In addition, these are likely to represent the key arterial routes into town and city centres; hence new cycleways on these roads could result in large increases in cycling volumes.

How does the tool identify what a ‘cohesive network’ might look like?

The tool also identifies what a ‘cohesive network’ for cycling might look like if we were to consider a wider range of interventions such as closing roads to motorised traffic and creating one-way systems. Unlike the ‘top ranked new cycleways’ layer, the cohesive network comprises all of the major high cycle potential corridors, including sections where the roads are narrower.

The layer was generated by joining up roads that have a high cycling potential on some or all their length. The ‘cohesive network’ might help authorities considering area-wide interventions such as pedestrian and cycle zones or modal filters.

How can I find the results for my area?

Results for each combined and local authorities can be accessed by clicking on the relevant area from the map below or search the authority’s name from the list below. This opens a separate webpage presenting a map of the areas identifying ‘existing cycleways’, ‘top ranked new cycleways’ and the ‘cohesive network’. It also presents a table providing various data about the top ranked new cycleways including the cycling potential, length of continuous cycle network (including the existing network), current speed limit and whether the road is wide and/or has spare road lanes.

How should I use these results?

Authorities may wish to use results from the tool to help prioritise their bids for Tranche 2 of the Emergency Active Travel Fund, complementing local knowledge and stakeholder engagement.

For example, authorities considering new cycleways may want to review the ‘top ranked new cycleways’ to inform their decision where best to invest. The table below the maps allows users to rank potential new cycleways by various metrics including:

In addition, the table provides information about road speed limits, width and road lanes which might help users filter out locations which are less desirable for them. For example:

Additionally, authorities considering area-wide measures may wish to consider the data for the ‘cohesive network’. Currently the tool cannot identify specific interventions to promote cycling (e.g. such as pedestrian and cycle zones or modal filters); however, it should give an indication of where such measures might add greatest value.

What are the key limitations of the tool?

Where can I find further information about the tool?

The technical specification for the Rapid Cycleway Prioritisation Tool can be found here, providing further detail about the assumptions underlying the tool.

A webinar about the Rapid Cycleway Prioritisation Tool is being held on 17th June 2020 from 10:30-11:45. Sign-up details can be found here and recording of the webinar will be available on the website after the event.

Data about the tools informing the model can be found here:

For expert users, the code underlying the project can be accessed here. If you would like to support the project with technical input, please provide feedback via the GitHub issue tracker. Data generated by the project can be downloaded from GitHub (e.g. see GeoJSON files for London here).

Use the tool

To use the tool, click on the region of interest below and click on the link (www.cyipt.bike/rapid/west-yorkshire for West Yorkshire, for example). Explore the results in the new page that appears with reference to the guidance on this page and the Rapid Cycleway Prioritisation Tool report.

Acknowledgments

Many thanks to Dr Malcolm Morgan (University of Leeds) and Martin Lucas-Smith (CycleStreets.net) for providing substantial input into methodological and web development aspects of the project respectively.

Thanks to Jeremy Clarke, Rabina Nawaz, John Sweetman and Richard Mace from the Department for Transport for vital input into the tool’s design. Thanks to Kevin McCann from Sustrans for guidance that improved the tool from a policy perspective. Thanks to Roger Geffen and others from CyclingUK for input into prototype versions of the tool.

Thanks to developers of open source software, especially to developers of the R language and the packages sf and tmap which underpinned the analysis. Thanks also to all the contributors to OpenStreetMap who provided open data on which much of the analysis was based, allowing publication of the results as open data under the conditions of the Open Data Commons Open Database License (ODbL 1.0). Data (c) OpenStreetMap contributors.