The Propensity to Cycle Tool: An open source online system for sustainable transport planning
LIDA researcher Dr Robin Lovelace is lead author on a recently published paper detailing the design, features and potential applications of The Propensity to Cycle Tool (PCT). The PCT was designed to assist transport planners and policy makers to prioritise investments and interventions to promote cycling. The tool answers the question: ‘where is cycling currently common and where does cycling have the greatest potential to grow?’
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.