We know quite a lot about how people use our road and rail networks. We can monitor toll-road capacities and collect Myki and Opal card data. But what about the walkers, the cyclists and the ride share users? And what do we really know about why people choose the transport methods they do?
Three years ago Rebecca Chau, a planner in our Melbourne office, began to notice gaps in the way we monitor and evaluate transport. Rebecca was living in New York at the time. The sheer connectedness of the city made her feel independent, empowered and safe. Her interaction with public transit was so much more than an origin and a destination but this data wasn’t being captured. Surely, Rebecca thought, this leads to plenty of transport planning opportunities being missed?
When Rebecca returned to Melbourne the following year, she set about proving her hypothesis. Working with our digital and planning teams, Rebecca put together a pilot study inviting 300 transit passengers to download a smartphone app and share their travel behaviour using GPS data. We collected and wove together travel insights from this data. Whenever a transport journey stood out from the norm, Rebecca contacted the participant to ask as simple question—why?
What she found were a number of unexpected fringe cases. For example, a participant with a two hour work commute might sometimes take an even longer route to and from work. Why? The longer route passed by venues that were opened at 5 a.m. meaning the commuter had the opportunity to use the bathroom or charge their phone.
If we want to truly understand the way people get around the city, we need to dig deeper than simply asking where they are going. We need to ask how they choose to get there and why.
What sets Rebecca’s method apart is that it allows her and the team to collect very specific data on very specific people (with their permission, of course!) The team is using this data to build a nuanced picture of how people are - and would like to be - using their transit networks.
Since the original proof of concept, the method has been refined and applied to a number of different transport context. Looking at bus ridership in Sydney the team was able to identify when and why riders chose to take an alternative methods of transport even where bus routes do exist. Better understanding people's relationship with buses allowed us to offer the consortium who commissioned the study a number of suggestions around how to improve their service for riders.
The project has also helped us to understand the motivation for other mobility patterns. We recently completed a study in collaboration with Transport for Victoria, where we used this method to better understand local behaviour. In a particularly fascinating insight, the data demonstrated that families are far more likely to take a cycling or walking trip if there are various points of interest along the way. This might include an overpass to count cars from or a park filled with possums. These findings have big implications for health, wellbeing and inclusion, and introduce a question rarely considered in transport planning: how do we design for novelty?
From airports, to cities, to corridors, by understanding a community's transport needs we can make much more informed decisions about what future infrastructure projects should look like. This will allow us to make much wiser and more meaningful investments in these spaces.
Perhaps the most important outcome of Rebecca’s method is that it isn’t limited to transport and mobility at all. She’s seen interest from the water and the energy sector. Whenever there are people within your network, understanding their needs is integral to your success.
The outcomes can be built form solutions like the perfectly placed transport corridor or services like additional washroom facilities at the train station after hours. They might even affirm that you know your user better than you thought. The end result is a more delightful transport and mobility experience—and a more inclusive and efficient built environment.
Rebecca’s study isn’t the first time an organisation has attempted to zoom in on an individual’s travel behaviour. Transport for Victoria conducts the Victorian Integrated Survey of Travel and Activity (VISTA) which asks randomly selected households to complete a travel diary for a single, specified day.
This method is great for capturing insights from a sample size in the thousands. However, when people are asked to remember and write down all the trips they took in a particular day, some of that information gets missed. Recording trips also doesn't provide an understanding of why people made the transit choices they did.
We want to supplement these methods to capture a more complete story. To do that, we needed a robust data source. Rebecca's original pilot study used a stock app. In subsequent studies, she worked with our digital team to build custom Android and iPhone apps capable of collecting more sophisticated user GPS data.
The team also created a machine learning model capable of sorting the data by trip and transport method in order to filter out specific insights. In a recent study conducted with Transport for Victoria the team collected nearly 7 million data points from 400 transport users over two weeks.
The video below plots the data collected by the team across one of their studies in Melbourne.
This story was written by Jeff McAllister, as part of the Research Review. This series is produced by the Arup Australasia Research team; Alex Sinickas, Bree Trevena and Jeff McAllister with contributions from Sheda and Noel Smyth.
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