Propensity to cycle tool (PCT)

The Propensity to Cycle Tool (PCT) aims to assist transport planners, policymakers, and researchers in identifying where cycling has the greatest potential for growth in urban areas. It allows users to measure and visualize cycling potential, taking into account various factors such as geographic location, topography, and existing cycling behaviour. Additionally, the tool quantifies the potential health and CO2 benefits associated with increased cycling uptake in different regions. It also supports scenario-based modelling, helping to estimate future cycling rates under different infrastructure and policy conditions.

Description of the tool

The Propensity to Cycle Tool is an open-source, web-based tool designed to support planning and decision-making in promoting cycling. It enables users to visualize cycling potential at high geographical resolution, from regional scales to specific street-level assessments. The tool is accessible online through an interactive map interface, allowing users to explore different areas and assess potential growth in cycling. The tool also supports scenario-based modelling, where users can simulate different scenarios (e.g., “Go Dutch,” increasing cycling rates similar to the Netherlands) to forecast future cycling patterns. As an open-source tool, the PCT allows advanced users to download data for in-depth analysis using GIS or statistical software, and the source code is freely available on GitHub. Users are encouraged to refer to the user manual for detailed instructions on how to interpret data and apply the tool effectively. 

How it works: inputs and outputs

Inputs: 

The key inputs for the PCT include geographic data (e.g., MSOA or LSOA levels), travel behaviour data (commuting and school travel based on the 2011 Census), topographical information (elevation and gradient), trip distance data, and scenario-based variables (e.g., the “Go Dutch” scenario, gender and age factors). 

Outputs:

The tool outputs include interactive maps showing areas with the highest potential for cycling growth, heatmaps indicating where cycling uptake could be most effective, and quantification of benefits in terms of health (physical activity) and CO2 reduction. It also provides downloadable data for further analysis using GIS or statistical software. Users can model future cycling patterns under different infrastructure scenarios, helping to inform decisions about investment in cycling infrastructure. 

Examples of use

The PCT has been used by local authorities, such as Transport for London and the city of Cambridge, to guide investment in cycling infrastructure and to forecast the impacts of proposed cycling interventions. A notable example includes the “Go Cambridge” scenario, which models the potential impact of a significant increase in cycling across the city, based on Dutch cycling behaviours. 

For more detail on the case studies and use of the tool in practice see: 

• PCT blog
• PCT manual