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 Fellow

Ali Abbas, University of Cambridge

Centre for Diet and Activity Research

James Woodcock, University of Cambridge

Centre for Diet and Activity Research

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