Propensity to Cycle Tool (PCT)

This article was published in 2018, in Newsletter 140.

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Over the last few years, a new online tool for Local Authorities and campaigners has been developed, called the Propensity to Cycle Tool (PCT).

The PCT is designed to help transport planners and policy-makers to prioritise investments and interventions to promote cycling. It answers the question: ‘where is cycling currently common and where does cycling have the greatest potential to grow?’.

It has been developed by an academic-led team involving the universities of Cambridge, Leeds and Westminster.

The PCT lives at www.pct.bike – check it out!

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Overview – where should we prioritise investment?

The PCT is a strategic planning tool. Different visions of the future are represented through various scenarios of change, including the Department for Transport (DfT) draft Cycling Delivery Plan target to double cycling in a decade and the more ambitious ‘Go Dutch’ scenario, wherein Dutch cycling levels are reached in England (allowing for English hilliness and trip distances).

By showing what the rate of cycling could feasibly look like in different parts of cities and regions, and illustrating the associated increase in cycle use on the road network, the PCT should inform policies that seek a wider shift towards sustainable transport.

The PCT can also be used at a smaller scale. The chosen scenario’s level of commuter cycling along a particular road can be used to estimate the future modal share for cycling on that corridor. This can be compared with the current road layout, and used to consider re-allocation from less sustainable modes to cater for cycling growth. In other cases, low current or potential flows may indicate a barrier, such as a major road or railway, lengthening trips. This could be addressed through new infrastructure such as a pedestrian and cycle bridge.

Central to both strategic and smaller-scale use is the question of where to prioritise high-quality cycling infrastructure of sufficient capacity for a planned growth in cycling.

In summary, the PCT is a planning support system to improve cycling provision at many levels from regions to specific points on the road network.

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Using the Propensity to Cycle Tool

The PCT is best understood by using it to explore current cycling levels, at regional, area, desire line, route and route network levels. We will take a look at how the PCT works at each of these levels, after a brief look at the scenario results at the regional level (the scenarios are described in more detail in an academic paper – see references at the end).

Under the 2011 Census scenario, the PCT represents levels of cycling to work based on the Census. This is a reasonable proxy for levels of utility cycling overall. The team used origin-destination (OD) data from the Census as the basis of the PCT, as this is the best publicly available dataset on English travel patterns. The input data are described in the paper and can be freely downloaded from the official UK Data Service website.

The regional picture and scenarios

The first thing the user sees on the front page is a map of England, broken into 44 regions. We deliberately used fairly large regions because successful cycling plans should be strategic and joined up, covering both large areas and large spans of time. This discourages the stop-start investment plans that have typified funding for active travel.

By hovering over different regions, the user can see what the current level of cycling to work is. We can discover for instance that Cambridgeshire has a relatively high (but low by Dutch standards) level of cycling of 9.7%, but that West Yorkshire has a low current level of cycling to work, 1.3% in the 2011 Census.

A key feature of the PCT is its ability to allow the user to imagine ‘cycling futures’. This can be seen on the front page map by clicking on the different scenarios (set to Census 2011 by default). We can see, for example, that under the government target to double cycling levels by 2025, West Yorkshire’s level would rise to 3.3% (more than a doubling) whereas Cambridgeshire would see cycling levels grow to 13.7% (a larger rise in absolute terms):

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Under the Go Dutch scenarios, these regions would see 23.1% (for Cambridgeshire) and 13.5% (West Yorkshire) of people cycling to work. This represents a huge levelling-out of cycling levels across the country, but still highlights the fact that some regions have higher cycling potential than others, owing to average trip distances and levels of hilliness.

Cycling levels by region

Click on a region such as Cambridgeshire. This shows the levels of cycling to work from the 2011 Census for each area of the county.

It shows that Cambridgeshire as a whole has fairly moderate levels of cycling to work, hovering around 5% in most places, well below Cambridge and the surrounding area. As we get nearer to Cambridge, there is a cluster of zones with higher levels of cycling, but the percentage of people cycling as their main mode of travel to work reaches about 15%.

Cycling potential at the desire-line level

This is all useful information, especially when we look at how the cycling potential could shift in the future. However, it provides little information about where current and future cyclists actually go.

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This is where the desire-line level can be useful. This can be selected by clicking on the Straight Lines option from the Cycling Flows dropdown menu. The results (zoomed in for north Cambridge) are shown .

What the above figures show is that as the level of cycling increases in a city, the spatial distribution of cycling can be expected to change. Under current conditions (whether related to socio-demographics, culture, infrastructure or other factors), cycling in Cambridgeshire is dominated by the Cambridge area. Yet there are clearly many short trips taking place into the city, as illustrated by the high cycling potential around the city under the Go Dutch scenario (here shown without the desire lines switched on):

Scenarios

There are in fact four scenarios presented, each of which enables us to predict the effect of cycling levels based on different levels of potential investment:

  • government target: models a doubling of cycling nationally, corresponding to the proposed target in the English Department for Transport’s draft Cycling Delivery Plan to double cycling in England between 2013 to 2025;
  • gender equality: seeks to capture a situation in which gender disparities are eliminated;
  • Go Dutch: what would happen if areas had investment bringing the same infrastructure and cycling culture as the Netherlands;
  • e-bikes: models the additional increase in cycling that would be achieved through the widespread uptake of electric cycles, built as an extension of the Go Dutch scenario.

Allocating cycling potential to the route network

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We know from Census data how many people cycle from A to B, but we have very little idea of how they are likely to travel. This is where the routing algorithm of www.CycleStreets.net comes in handy. The PCT uses the CycleStreets cycle routing data interface (API) to estimate the ‘fastest’ route for all short (well, up to 20 km) desire lines in England.

Not only does www.CycleStreets.net allow us to find all the fastest routes, It also represents a good indication of where new infrastructure should be built, as people (especially women and the elderly) have a strong preference for cycling along the most direct routes.

The result of all this routing work is illustrated in the future scenario above, which shows the fastest and quietest routes associated with the most-cycled routes in Cambridge.

Closer detail

Perhaps the most important layer of the PCT is the LSOA Route Network layer (LSOA stands for ‘Lower Layer Super Output Area’, covering roughly 3,000 people), which provides a nationwide map of cycling potential at the route network level.

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This is illustrated under 2011 and e-bike scenarios in central Cambridge in the figure (right). Note the high levels of cycling correctly identified in the potential bottleneck at the railway crossing, highlighting the importance of Mill Road bridge:

Only the passage of time, and people’s commitment (hopefully informed by models such as the PCT) to sustainable travel, will help turn the estimates of cycling levels under various cycling futures (including Go Dutch) into reality.

Future plans

Future DfT-funded plans for the PCT include a ‘Schools layer’ that will estimate cycling potential to school. This will help flag residential routes and ‘orbital’ routes in need of infrastructure to complement the networks highlighted by commuter cycling, which tends to emphasise arterial routes into major employment centres.

A related new project, the Cycling Infrastructure Prioritisation Tool (CyIPT), has been developed to prototype level. This aims to suggest specific infrastructure that could be achieved, rather than the broader areas that the PCT provides. See: www.cyipt.bike.

More information

You can get updates about the tool at www.blog.pct.bike. To view the underlying source code, please visit www.github.com/npct – the codebase and models are all open source.

Reference

Lovelace, R., Goodman, A., Aldred, R., Berkoff, N., Abbas, A., Woodcock, J., 2017. The Propensity to Cycle Tool: An open source online system for sustainable transport planning. Journal of Transport and Land Use. 10:1, 505-528, DOI: 10.5198/jtlu.2016.862.

Martin Lucas-Smith