4.1 Article

The Propensity to Cycle Tool: An open source online system for sustainable transport planning

期刊

JOURNAL OF TRANSPORT AND LAND USE
卷 10, 期 1, 页码 505-528

出版社

UNIV MINNESOTA, CENTER TRANSPORTATION STUDIES
DOI: 10.5198/jtlu.2016.862

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资金

  1. Department for Transport [RM5019SO7766]
  2. Consumer Data Research Centre (ESRC) [ES/L011891/1]
  3. MRC Population Health Scientist Fellowship
  4. Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence - British Heart Foundation
  5. Cancer Research UK
  6. Economic and Social Research Council
  7. Medical Research Council
  8. National Institute for Health Research (NIHR)
  9. Wellcome Trust
  10. NIHR
  11. Economic and Social Research Council [ES/G007462/1, ES/K004549/1] Funding Source: researchfish
  12. Engineering and Physical Sciences Research Council [EP/K503757/1] Funding Source: researchfish
  13. Medical Research Council [MR/K021796/1] Funding Source: researchfish
  14. ESRC [ES/K004549/1, ES/G007462/1, ES/L011891/1] Funding Source: UKRI
  15. MRC [MR/K021796/1] Funding Source: UKRI

向作者/读者索取更多资源

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.. is 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.

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