• 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?

• In January 2015 we were commissioned by the Department for Transport
• In April 2017 the Propensity to Cycle Tool is finally officially launched
• As part of the UK's Cycling and Walking Infrastructure Strategy (CWIS)
• Our tool is a key part of the local implementation (quote below from the Transport Minister Chris Grayling)

£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.

• From the World Health Organisation's Constitution, 1946 (Grad 2002).

• We need to shift towards tackling the root causes of bad health

• Rather than "fixing people who've fallen off a cliff"

• Good (and bad) health behaviours are learned early on -> work of SickKids = vital

Source: Campaign for Better Transport

• AURIN
• Leeds-Bradford cycle path interactive map
• DECC's 'Energy 2050' planning tool
• Walkability index site walkscore.com (Leeds has 99% walkability!)
• Interactive download of bicycle paths (but for research?): https://www.velomap.org/

• If the data underlying policy is hidden, it can be represented to push certain aims (solved by open data)

• If the data is 'open' but the tools are closed, results open to political influence

• Which brings us onto our next topic…

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)
           ...

• 2018: (Global PCT?)

• Academic write-up (Lovelace et al. 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

Robin Lovelace (Lead Developer, University of Leeds)

• James Woodcock (Principal Investigator, Cambridge University)
• Anna Goodman (Lead Data Analyst, LSHTM)
• Rachel Aldred (Lead Policy and Practice, Westminster University)
• Ali Abbas (User Interface, University of Cambridge)
• Alvaro Ullrich (Data Management, University of Cambridge)
• Nikolai Berkoff (System Architecture, Independent Developer)
• Malcolm Morgan (GIS and infrastructure expert, UoL)

"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."

• Shane Snow: Head of Seamless Travel Team, Sustainable and Acessible Travel Division

"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

Included in Cycling and Walking Infrastructure Strategy (CWIS) and the Local Cycling and Walking Infrastructure Plan (LCWIP)

Shows on the map where there is high cycling potential, for 4 scenarios of change

• Government Target
• Gender Equality
• Go Dutch
• Ebikes

• Origin-destination data shows 'desire lines'
• How will these shift with cycling uptake

• Test version of pct.bike

• PCT covers 'where'. Cycling Infrastructure Prioritisation Toolkit (CyIPT): DfT-funded toolkit for cycling infrastructure prioritisation in progress
• Combines many datasets ("PCT + Infra") to identify 'low hanging fruit'

"few studies link ridership with newer (innovative) types of infra- structure, particularly intersection treatments. More research is needed on the effect of bicycle-specific treatments, including bike boxes, traffic signals, and two-stage queue boxes, and treatments where cycle tracks reach intersections"

• But whole network design found to be important (Buehler and Dill 2016).

1. Use existing interactive on-line tools such as the Propensity to Cycle Tool. Download and explore open data data.
2. Design for the long term - have a vision and prioritise it
3. Experiment, monitor, adapt. (See experimental Traffic Regulation Order (TRO) case in Tavistock Place)
4. Get yourself and team skilled up in open source software
5. Collaborate