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P71 The propensity to cycle tool: a policy tool to estimate cycling potential for english and welsh transport planners
  1. J Woodcock1,
  2. R Aldred2,
  3. R Lovelace3,
  4. A Goodman4
  1. 1MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
  2. 2Active Travel Academy, University of Westminster, London, UK
  3. 3Institute of Transport Studies, University of Leeds, Leeds, UK
  4. 4Department of Population Health, London School of Hygiene and Tropical Medicine, London, UK


Background Getting people cycling is an increasingly common objective in transport planning. A growing evidence base indicates that high quality infrastructure can boost cycling rates. Yet for measures to be effective, it is important to intervene in the right places. This creates the need for tools and methods to help answer the question ‘where to build?’

The Propensity to Cycle Tool (PCT) is an open source, freely available, interactive tool to help prioritise cycling in England and Wales, covering both commuting and travel to school. In addition to the tool the data are available as download to allow more detailed GIS analysis. It was created by an academic team for the Department for Transport.

Methods The PCT uses origin data from the 2011 Census on main mode of travel to work and the 2011 National School Census covering all state-schools in England. We modelled propensity to cycle as a function of route distance and hilliness between home and school or work. We generated scenarios, e.g. ‘Go Dutch’ – in which people in England were as likely to cycle as theDutch, accounting for trip distance and hilliness. We did this based on a synthetic microsimulation population, allowing flexible scenarios and more accurate impact calculations.

We estimated changes in the level of cycling, walking, and driving, and associated impacts on physical activity and carbon emissions. For adults we estimated health economic benefits from reductions in premature mortality and sickness absence from increases in physical activity. Health outcomes were calculated using a bespoke and improved version of the UK Transport Appraisal Guidance (originally based on the WHO HEAT tool). Our improvements include using individual level rather than aggregate data, ebikes, integrating health gains from cycling with losses from less walking, and adjusting physical activity levels for route hilliness.

Results The PCT scenarios show the substantial potential for increases in cycling and the large benefits that this could realise. For example in 2011, 1.8% of children cycled to school. Under the Go Dutch scenario, this would rise to 41.0%. This would increase physical activity from school travel among pupils by 57%, and reduce transport-related carbon emissions by 81 kilotonnes/year. These impacts would be substantially larger in secondary schools than primary schools (a 96% vs. 9% increase in physical activity, respectively).

Conclusion The PCT is currently used by over 60 local authorities in England and Wales, and is contributing to the development of local policies as part of the Cycling and Walking Investment Strategy.

  • cycling
  • policy
  • health impact modelling
  • GIS
  • tools

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