The unique challenges facing walk and cycle planners

All over the world, there’s a growing need (and desire) for more sustainable transport networks. Supporting and encouraging walk and cycle trips is a crucial part of this process – helping to reduce private vehicle use and improve the health of communities and individuals chief among them – but doing so is a complex and sometimes frustrating process.

So, even though making more accessible and efficient walk and cycle networks is recognised as a priority for places all over the world, why is it so challenging and what can be done about it?

Data availability and quality

The saying ‘what gets measured gets managed’ holds more than a kernel of truth when it comes to planning walk and cycle networks. Historically, there’s been a lack of dedicated data available to active transport planners, which in turn has impacted their ability to investigate areas of analysis and understand current walk and cycle trends. When compared to the amount of data dedicated to road travel (which is made easier by the nature of road networks and well-established methods of measurement), active transport trip volumes and routes are poorly understood.

Thanks to the rise of new geospatial datasets like GPS mobility data, targeted datasets like Strava, as well as an increase in walk and cycle counts, however, this gap in data quality and availability is slowly closing. Mobility datasets like People Movement Data give planners the ability to investigate movement patterns at both a granular and holistic level and then connect those movements with the time at which they happen. This kind of rich, multidimensional data makes it possible to glean widespread, evidence-based insights on walk and cycle travel patterns because they make it possible to easily and accurately identify high and low-performing areas within active transport networks. However, the utilisation of these datasets in targeted, intelligent ways for walk and cycle planning is still a developing sector of the industry.

Lack of purpose-built modelling tools

Predicting future walk and cycle trips is a complex task that’s made all the more challenging without a comprehensive understanding of current trip volumes and travel patterns (as well as get a more nuanced understanding of what influences those trips). This is a well-known conundrum to the planners responsible for maintaining and improving walk and cycle networks, and it’s a strong contributor to the relative dearth of purpose-built walk and cycle modelling tools.

This gap is closing, however, with large datasets that capture walk and cycle trips more accessible and usable than ever before. By combining these with dedicated active transport scenario planning tools, planners’ ability to test specific changes to those networks and forecast future active transport trips is poised to rapidly evolve. Being able to quantify the benefits of specific changes to walk and cycle networks makes it easier to identify and prioritise potential projects. Perhaps more importantly, by understanding the value of adding or improving walk and cycle infrastructure, planners can confidently justify investment decisions and make impactful changes that help foster active transport.

The Planwisely team is working on a solution to these pervasive challenges with a tool called PATH, which will allow planners to analyse current walk and cycle networks and test the impact of potential network or land use changes on these movements. By harnessing Planwisely’s powerful mapping engine and user-friendly front-end, PATH will make walk and cycle planning more accessible  and effective, helping to support complex planning and investment decisions and drive active transport uptake.