It’s hard to capture what good news this is. Through a bipartisan bill, Congress is seriously considering a plan to give more weight to how proposed transit investments improve access to jobs and opportunity. The bureaucratic word for this is accessibility, but I like to call it physical freedom, because the presence of meaningful choices in your life lies in whether you can get to them in a reasonable time, which is exactly what this measures. From the Transportation For America website:
The incredibly blunt metrics that most planners or communities have used since the 1960s, like overall traffic congestion and on-time performance for transit, paint a grossly two-dimensional picture of the challenges people face while trying to reach jobs and services. They don’t provide sufficient information for agencies to make accurate decisions about what to build in order to best connect people to the places they need to go. These 1960s metrics lead to singular and expensive solutions (like highway expansions), while often failing to solve the problem or even creating new ones.
Today, precise new tools allow communities to accurately calculate accessibility to employment opportunities, daily errands, public services, and much more. These tools allow states and MPOs to better understand where people are traveling and to design transportation networks to maximize the ability of people to travel. It also allows states and MPOs to optimize their transportation networks to utilize all modes of transportation and even to understand how their investments interact with land use policies.
We use these tools all the time in our bus network redesigns, though we are limited, by available data, to studying access to jobs. It is great to see people working on better data layers to capture errands, shopping, and so on. I am not sure how much of this granularity is necessary, but it doesn’t hurt.
Implicit in this news is the idea that ridership prediction could decline in importance, which would be great news. We are much too deferential to predictive algorithms for things that may not be predictable, such as human preferences and attitudes 20 or 30 years from now.
There’s one other caution. When planning fixed infrastructure investment, hard thinking has to go into what facts from today are assumed to be permanent. For example, when we talk about access to public services, will we just analyze outcomes based on the often terrible locations of these services, thereby enabling continued terrible location decisions? If we dare to predict better urban form in response to public investments, on what basis will we predict that?
The conversation about access therefore needs to reflect on what aspects of urban form and location are likely to last for decades, like the larger scale urban form and the likely trip generation it implies. (We may build more dense urban fabric, but we are unlikely to tear it down.) This is another reason why too much granularity could distract us; it leads us back into obsessive descriptions of the present, some aspects of which could be different next year.
So this is difficult philosophical stuff. I’m trying to grapple with it in the next book. Feel free to nag me about how it’s going!
Thanks for the tidbit! I hope that accessibility continues to grow in the planning profession, fueled by better data and better tools.
How goes the book on it?