How to use the Propensity to Cycle Tool (PCT)

The material here was developed during 2016 and 2019 for use in training. To request more information or provide feedback, please email us at pct@pct.bike or report issues on our GitHub issue tracker. The PCT also has a blog, which contains further information on some of the topics featured in the case studies and FAQs. Contributions to GitHub, the blog or other parts of the project are welcome.

PCT Essentials

  • Read our two pager Essentials document first, for a high level summary

User Manuals and Training Materials

Version 1.4 for English, version 1.2 for Welsh

Case Studies

The case studies use the interface and particularly the data downloads (as CSV or geojson files) to carry out analysis of specific places (including areas/routes). They cover London boroughs, large city-regions, smaller cities and towns, and rural areas.
  • Bournemouth Case Study compares area-level school and commuter cycling potential in Bournemouth.
  • Cornwall Case Study compares area-level commuter cycling potential across five Cornish towns earmarked for investment.
  • Ealing Case Study examines area- and route-level commuter cycling potential in Ealing, West London, and associated benefits.
  • Greater Manchester Case Study analysis area- and route-level cycling commuting in the GM city-region, including a focus on key urban district centres.
  • Hereford Case Study is an example of using the PCT to help identify a priority cycle network in small cities, using the schools and commuting layers.
  • Hounslow Case Study covers area and route-based cycle commuting potential, incorporating the impact of increased employment at Heathrow Airport on car and cycle trips.
  • Kenilworth Case Study identifies high potential areas and routes in this town of 22,000 people, and discusses implications for infrastructure prioritisation.
  • Newham Case Study examines commuter cycling potential across Newham in East London.
  • Preston Case Study covers cycle commuting potential in the city of Preston, including an analysis of quiet route detour factors and potential priority corridors.
  • Rotherhithe Case Study looks at how a then-planned Canary Wharf-Rotherhithe bridge might affect commuter cycling potential, incorporating projected population growth.
  • Southwark Case Study (in collaboration with Transport for Quality of Life) shows how modelled PCT data can be combined with manual count data to conduct a controlled before-and-after study into the impact of modal filters on cycling.
  • Tunbridge Wells Case Study conducts some bespoke analysis looking at the potential for commuters to cycle to local stations instead of driving there.
  • West Sussex Case Study uses the ‘e-bike’ scenario to examine the potential for commuter cycling and its benefits, and outline a potential priority route network; including a specific case study (the A264 corridor).


1. Does hilliness matter for cycling? Do the Dutch just cycle more because the Netherlands is flatter?

2. How does propensity to cycle differ between England and the Netherlands?

3. Why focus on the fast routes?

4. What if I'm interested in trips not people? And does PCT account for return trips?

About the Propensity to Cycle Tool

This is the online home of the open source transport planning system, the Propensity to Cycle Tool (PCT). The PCT is released under the Affero GPL: it is free to use, copy and modify, e.g. to create versions for new cities and states. Please cite the journal article Lovelace et al. (2017) and/or Goodman et al. (2019) if you use the PCT in your work.

The PCT Team

Co-investigator: Data Lead
Co-investigator: Lead Developer
Co-investigator: Lead Policy and Practice
With many thanks also to former PCT team members Alvaro Ullrich and Ilan Fridman Rojas

Aim and scope of the PCT

The PCT was designed to assist transport planners and policy makers to prioritise investments and interventions to promote cycling. The PCT answers the question: 'where is cycling currently common and where does cycling have the greatest potential to grow?'. The PCT can be used at different scales.

First, the PCT is a strategic planning tool. Different visions of the future are represented through various scenarios of change, including the Department for Transport’s draft Cycling Delivery Plan target to double cycling in a decade and the more ambitious ‘Go Dutch’ scenario, whereby cycling levels equivalent to the Netherlands are reached in England and Wales (allowing for English and Welsh hilliness and trip distances). By showing what the rate of cycling could feasibly look like in different parts of cities and regions, and illustrating the associated increase in cycle use on the road network, the PCT should inform policies that seek a wider shift towards sustainable transport.

Second, the PCT can also be used at a smaller scale. The scenario level of commuter cycling along a particular road can be used to estimate future mode share for cycling on that corridor. This can be compared with current allocation of space to different modes, and used to consider re -allocation from less sustainable modes to cater for cycling growth. In other cases, low current or potential flows may indicate a barrier, such as a major road or rail line, causing severance and lengthening trips. This could be addressed through new infrastructure such as a pedestrian and cycle bridge.

Central both to strategic and smaller-scale use is the question of where to prioritise high quality cycling infrastructure of sufficient capacity for a planned growth in cycling (Aldred et al 2017).

In summary the PCT is a planning support system to improve cycling provision at many levels from regions to specific points on the road network. For further information on the thinking underlying the tool's design, and the methodology used to create it, please see Lovelace et al. (2017) (commute layer) and Goodman et al. (2019) (school layer). You can get updates about the tool on the PCT's blog series. To view the underlying source code, please visit Github/npct.

Funding & Acknowledgements

The work was initially funded by the English Department for Transport (DfT) to create the National Propensity to Cycle Tool for England (2015-2017, with further funding in 2018-19). The Welsh government funded the extension to Wales in 2018. We would also like to thank the EPSRC and ESRC for Impact Acceleration funding (2016-2017).

We would like to thank Brook Lyndhurst for facilitating Phase 1 of the DfT contract and Atkins for facilitating Phase 2.

We would like to acknowledge the support and encouragement we have had from Shane Snow, Philipp Thiessen, Richard Mace, Kaylisha Archer, John Sweetman, Rabina Nawaz and colleagues at the Department for Transport (DfT).

Finally, we would like to thank CycleStreets for providing data on routes.

Scope, limitations and liability

The PCT uses transparent methods and reliable, tested data. However, the tool is limited in scope: the PCT is based on hypothetical national scenarios of cycling uptake. It is not a predictive tool and does not provide estimates of cycling uptake resulting from a given intervention. The PCT is limited by the geographic resolution of the origin-destination data it uses, and uses a deterministic (not probabilistic) routing algorithm. Thus, care should be taken when using the PCT to plan for specific interventions, for example estimating cycling potential on two parallel streets. The tool is designed to support planning based on local knowledge and we cannot accept liability for any loss or damage caused.

Accessibility Statement

The accessibility statement is available online.

Contact Us

For more information or questions, please contact us at: pct@pct.bike.


Aldred, R., Elliott, B., Woodcock, J., Goodman, A., 2017. Cycling Provision Separated From Motor Traffic: a systematic review exploring whether stated preferences vary by gender and age.Transport Reviews. 37:1, 29-55, DOI: 10.1080/01441647.2016.1200156.

Lovelace, R., Goodman, A., Aldred, R., Berkoff, N., Abbas, A., Woodcock, J., 2017.The Propensity to Cycle Tool: An open source online system for sustainable transport planning. Journal of Transport and Land Use. 10:1, 505–528, DOI: 10.5198/jtlu.2016.862.

Goodman, A., Fridman Rojas, I., Woodcock, J., Aldred, R., Berkoff, N., Morgan, M., Abbas, A., Lovelace, R., 2019.Scenarios of cycling to school in England, and associated health and carbon impacts: Application of the ‘Propensity to Cycle Tool’. Journal of Transport & Health. 12, 263-278, DOI: 10.1016/j.jth.2019.01.008.