- Existing tools for planning
- A case study of the PCT
- Future directions
- But first: a test of interactivity
- Who uses (broadly defined) tools for policy-making?
- What % of those are open access?
- Open source?
Toronto General Hospital to the world via webinar, 2017-05-12
£1m Big Bike Revival funding will help people get back in the saddle and make cycling the natural choice https://t.co/BYZDk9NqHK #CWIS pic.twitter.com/UNp6jyXPnd— Dept for Transport (( ???)) April 21, 2017
A state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity.
Source: Campaign for Better Transport
A life-course of my involvement with the PCT
Concept of algorithms for cycling uptake (PhD 2009 - 2013) Discovery of programming (R) and shiny (2013) 'Propensity to Cycle' bid by DfT via SDG (2014) Start work w. Cambridge University and colleagues (2015) Implementation on national OD dataset, 700k routes (2016) Addition of school and near-market prototypes (late 2016) LSOA phase (Malcolm Morgan) (early 2017) ...
Propensity to cycle refers to the modelled uptake of cycling at area, desire line and route network levels under different scenarios of the future. Policy relevant scenarios include meeting national or local targets, the potential uptake if people in the study area cycled as much as the Dutch do or the impact of electric bikes on people's willingness to cycle longer distances. (see Get Britain Cycling article, 2016)
The tool aims to help prioritise where interventions are most needed based on where cyclable trips are most common
“The PCT shows the country’s great potential to get on their bikes, highlights the areas of highest possible growth and will be a useful innovation for local authorities to get the greatest bang for their buck from cycling investments and realise cycling potential.” Andrew Jones, Parliamentary Under Secretary of State for Transport
“A world first from a brilliant academic team. As a Department we should be celebrating this example of innovation in promoting the UK’s capability to deliver innovation in transport planning.” Pauline Reeves, DfT Deputy Director Sustainable Accessible Transport
|Tool||Scale||Coverage||Public access||Format of output||Levels of analysis||Software licence|
|Propensity to Cycle Tool||National||England||Yes||Online map||A, OD, R, RN||Open source|
|Prioritization Index||City||Montreal||No||GIS-based||P, A, R||Proprietary|
|PAT||Local||Parts of Dublin||No||GIS-based||A, OD, R||Proprietary|
|Usage intensity index||City||Belo Horizonte||No||GIS-based||A, OD, R, I||Proprietary|
|Bicycle share model||National||England, Wales||No||Static||A, R||Unknown|
|Cycling Potential Tool||City||London||No||Static||A, I||Unknown|
|Santa Monica model||City||Santa Monica||No||Static||P, OD, A||Unknown|
Robin Lovelace (Lead Developer, University of Leeds)
"The PCT is a brilliant example of using Big Data to better plan infrastructure investment. It will allow us to have more confidence that new schemes are built in places and along travel corridors where there is high latent demand."
"The PCT shows the country’s great potential to get on their bikes, highlights the areas of highest possible growth and will be a useful innovation for local authorities to get the greatest bang for their buck from cycling investments and realise cycling potential."
Included in Cycling and Walking Infrastructure Strategy (CWIS) and the Local Cycling and Walking Infrastructure Plan (LCWIP)