The Propensity to Cycle Tool: An open source online system for sustainable transport planning
Robin Lovelace
University of Leeds
http://orcid.org/0000-0001-5679-6536
Anna Goodman
London School of Hygiene and Tropical Medicine
Rachel Aldred
University of Westminster
Nikolai Berkoff
Independent web developer
Ali Abbas
University of Cambridge
James Woodcock
University of Cambridge
DOI: https://doi.org/10.5198/jtlu.2016.862
Keywords: Cycling, Planning, Modelling, Participatory
Abstract
Getting people cycling is an increasingly common objective in transport planning institutions worldwide. A growing evidence base indicates that high quality infrastructure can boost local cycling rates. Yet for infrastructure and other cycling measures to be effective, it is important to intervene in the right places, such as along ‘desire lines’ of high latent demand. This creates the need for tools and methods to help answer the question ‘where to build?’. Following a brief review of the policy and research context related to this question, this paper describes the design, features and potential applications of such a tool. The Propensity to Cycle Tool (PCT) is an online, interactive planning support system that was initially developed to explore and map cycling potential across England (see www.pct.bike). Based on origin-destination data it models cycling levels at area, desire line, route and route network levels, for current levels of cycling, and for scenario-based ‘cycling futures.’ Four scenarios are presented, including ‘Go Dutch’ and ‘Ebikes,’ which explore what would happen if English people had the same propensity to cycle as Dutch people and the potential impact of electric cycles on cycling uptake. The cost effectiveness of investment depends not only on the number of additional trips cycled, but on wider impacts such as health and carbon benefits. The PCT reports these at area, desire line, and route level for each scenario. The PCT is open source, facilitating the creation of scenarios and deployment in new contexts. We conclude that the PCT illustrates the potential of online tools to inform transport decisions and raises the wider issue of how models should be used in transport planning.Author Biographies
Robin Lovelace, University of Leeds
Consumer Data Research Centre, Research FellowAli Abbas, University of Cambridge
Centre for Diet and Activity ResearchJames Woodcock, University of Cambridge
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