The National Propensity to Cycle Tool (NPCT) is an online, open source system for prioritising investment in new cycle-friendly infrastructure.
The tool, which is funded by the Department for Transport does this by modelling cycling ‘desire lines’ and displaying the results at area to route levels. The results of various future scenarios are presented on an online interactive map, assisting the decision making process at local, city and regional levels.
What does it do?
The tool was built specifically for cycling but could be used to represent other modes of travel, from walking to car sharing. In the default scenario it shows the current rate of commuter cycling across zones in the region of interest, indicating where cycling is most common and providing a visualisation of the desire lines of highest demand.
The tool provides a range of scenarios when specific barriers are removed – for example if one takes e-bikes in to account, removes socio-cultural barriers or overcome the tendency for women to cycle less than men.
As a result, the tool can help target specific areas and routes with high cycling potential, and thus facilitate strategic long-term planning.
How was it developed?
The tool was developed using a number of recently released open source software products such as Leaflet and Shiny and is based on the statistical programming language R. The complete code-base is available online.
Routing was done using the CycleStreets.net API to show the possible routes taken from home to the workplace.
What makes it special?
The tool is unique because it can be used for strategic long-term planning to determine where new bicycle paths are most needed. Most transport models are expensive, proprietary and do not work online. Another novel feature of the method is its ability to quantify extra cycling potential along specific routes.
How can I use it?
The tool is now available online at http://pct.bike/
Who developed the tool?
Principal Investigator: Dr James Woodcock, CEDAR, University of Cambridge
Co-investigator – Lead Data Analyst: Dr Anna Goodman, LSHTM
Co-investigator – Lead Developer: Dr Robin Lovelace, University of Leeds
Co-investigator – Lead Policy and Practice: Dr Rachel Aldred, University of Westminster
Data Scientist / Developer: Ali Abbas, CEDAR, University of Cambridge
Web Developer: Dr Nikolai Birkoff,
Data Scientist: Alvaro Ullrich, CEDAR, University of Cambridge