Understanding the constant evolution of transport planning
November 11, 2022
This Transport Planning Day, Leigh Stolworthy looks at how the profession is evolving and outlines his needs for the future of the sector.
The last time I visited the Institution of Civil Engineer¡¯s building in Great George Street, Westminster in London was in the year 2000.
I was working as a Highways and Traffic Engineer at the time. I went there specifically to buy the book Highways Traffic Analysis and Design, 3rd Edition by the late Richard Salter and Nick Hounsell.
It was my go-to guide to plying my trade at that time and it covered everything from traffic surveys, the four-step modelling process, speed, flow and density theory, traffic signal design, congestion and more. It¡¯s a fantastic book and I still have it, but the world and our profession have changed a lot since then.
Change is constant
Back when the book was written, it was mostly about chasing capacity. If there are ¡°X¡± number of trips and ¡°Y¡± level of capacity on the road, the two must balance with a little bit of ¡°Y¡± left over.
The classic ¡®computer says road¡¯ approach and discussions on the implications of plus 2 degrees C certainly didn¡¯t feature much. At some point, I began to question why all those trips were at that point in a network, where they were all going to, coming from and whether it was possible to manipulate those reasons towards optimisation of movement, instead of proposing more roads which ultimately brings more cars because of that little bit of ¡°Y¡± left over.
This is a rabbit hole I happily fell into, navigating the triple access approach and trying to find ways to manipulate the relationships between mobility, proximity and digital-based access, urban efficiencies, as well as building strategies around it and trying to figure out how to measure change over time.
I¡¯m a sucker for complexity and it¡¯s probably the main reason I love my job.
Fast forward a couple of decades and we¡¯re finally (or still) talking about ¡®vision and validate¡¯ or ¡®decide and provide¡¯ or other variations on the theme of Theory of Change.
Develop a vision for the type of future we want to achieve, define possible characteristics of that future, scenario test them to choose the best range of characteristics, determine how different they are from today and design a pathway to achieving the change required.
Sounds simple enough. But, while we are still talking about this, are we actually doing it? If there is one thing I¡¯ve realised over the years, it¡¯s that innovation and ideas about doing things differently travel at much higher speeds than changes in policy, manuals and guidelines. A bold approach is always required.
We need to find better ways of understanding travel behaviour and the key decision drivers on how and why people choose to travel and how those behaviours are likely to change over time.
Getting to the root of the problem
A few years ago, I was fortunate to be able to participate in a course on Problem Driven Iterative Adaptation (PDIA) Methodology through Harvard University. A key step in the PDIA methodology is problem deconstruction. You can¡¯t expect to find the right solution to the problem if you don¡¯t truly understand the nuances of it. Otherwise, you end up with an innovation searching for an application and I¡¯m sure most of us can think of an example of one of those.
Whether you deconstruct the problem with the help of Ishikawa diagrams or intuitively, it is a critical step. With a ¡®vision and validate¡¯ approach, we need to deconstruct the transport future that we want to achieve to help us navigate there from today.
I¡¯ve mentioned the ¡®future that we want¡¯ several times so far and this is the difficult part, because how do we know what kind of future the people who will occupy it will want when they possibly don¡¯t even exist yet, or just don¡¯t have an option about it? The simple fact is that we can¡¯t, but we do know what aspects need to change and why they need to change.
How we give effect to that change is where the deep uncertainty comes in, because the rate of change of technology and systems and the unknown behaviour and aspirations of future generations are more dynamic.
A way to deal with this is through adaptive incrementalism that enables a shift in approach if the desired results are not being achieved. We can set mechanisms to measure this periodically and adapt approaches when required with one eye fixed on the transport future we are aiming for.
There are signs of the changing travel behaviour if we know where to look, with some more obvious than others, such as the effects of the pandemic. We need to find better ways of understanding travel behaviour and the key decision drivers on how and why people choose to travel and how those behaviours are likely to change over time. We can¡¯t assume that the travel patterns we observe are a reflection of preference either. People navigate the world as it exists, not necessarily how they would want to.
We can¡¯t assume that the travel patterns we observe are a reflection of preference. People navigate the world as it exists, not necessarily how they would want to.
Harnessing the power of data
Transport planning has evolved from capacity chasing to asking big questions about what people need to live their lives in an optimal way, with the most efficient access to the things they need. To this end, we need to find new ways and data sources to tap into that help us understand this better.
Data science is beginning to play a larger role in transport decision making with the potential to use less traditional data sets and sources to give a much richer understanding of the transport ecosystem and its users. We need to improve the balance between quantitative observed transport data and qualitative data about the people that use transport systems.
We may need to adjust the balance of effort and funding applied to new infrastructure versus improving and adapting the systems that operate on the infrastructure that we already have. This is already happening in the road-based environment with things like demand responsive transport, mobility as a service, electric micromobilty etc.
Can we sweat our assets in more efficient and carbon neutral ways with systems that work better for users?
When building new communities with better integration between land use and transport we can manage travel demand better, reduce travel distances and provide viable and healthy car alternatives at least for shorter trips, and perhaps by not providing that little bit of extra ¡®Y¡¯.
Future proofing anything is a tricky business. There are many examples of products and services that have fallen by the wayside and lost their relevance over time. But perhaps the future of transport can become less uncertain if it is by design.