Philosophy

Just “Prioritize Ridership”: Is it That Easy?

Matthew Yglesias thinks more carefully about transit than any other US pundit I’ve encountered at his level of celebrity, so his takes are often useful.  Today, he has a very broad one, called “American transit agencies should prioritize ridership over other goals.”  He begins:

Why does the United States struggle to create cost-effective rail infrastructure? Why do non-NYC American cities have such a hard time attracting mass transit ridership?

On one level, these are deep and complicated questions. But one thing I want to say to the growing community of people who are interested in them is that American agencies don’t deliver on these goals because this country’s high-level governance constructs don’t say they should deliver on them. Of course you won’t find a grant guideline that specifically says “don’t focus on delivering high ridership at an effective cost.” But wasting money is really, really easy when nobody is specifically telling you not to.

His piece spans a huge range of issues, from rail construction methods to bus service planning.  I agree with him about rail: We can do it cheaper by making stations more functional and less palatial, as long as we plan enough capacity.  On service planning, though, I think he oversimplifies in a way that lots of well-intentioned urban policy wonks oversimplify, so it’s worth unpacking a little.  There are two issues with saying “just prioritize ridership.”

  • Ridership is not very predictable.  That’s why, in our work, we prioritize access to opportunity instead.  Actual ridership is affected by lots of unpredictable external events (pandemics, economic conditions, etc), but access to opportunity is the constant thing that transit provides that is the foundation of ridership. Access is also important for a bunch of other policy reasons.
  • Low-ridership service is sometimes justified by policy goals that matter to people, including, in some cases, racial and social equity.

Yglesias cites my work on the ridership-coverage tradeoff:  In service planning, a ridership-maximizing network doesn’t go everywhere and serve everyone, because it goes where the most riders are and runs fast and direct enough to be useful to them.  So a ridership goal is in conflict with goals variously described as “leave nobody behind” or “meet the needs of low income people (wherever they are)” or “we pay taxes too so we should get some service.”  All those impulses lead to predictably low-ridership service, which I call coverage service.  I explain why this conflict is unavoidable here.

You will never hear me say, as Yglesias does, that ridership should be the only goal of a transit service, and not just because I’m a consultant who facilitates conversations on the topic.  I won’t say that because the decision is genuinely hard, and there are some good policy reasons for coverage services.

The suburbanization of poverty in many cities has increased the number of low-income people and people of color living in suburban land use patterns that are just inimical to public transit.  Those areas have fast roads that are unsafe to cross, no sidewalks, disconnected street patterns that obstruct walks to the stop, road patterns that require buses to make crazy loops, etc.  A strictly ridership-based approach would not go to a lot of those places, but will put lots of service in dense inner cities that happen to be increasingly gentrified.  The result can be something that is measurably inequitable by both race and income.  In other words, sometimes, in some common geographies, there’s a ridership vs equity tradeoff.   (We have some unpublished work on this for a major US transit agency that we hope to release soon.)

So when Yglesias says …

Now again, I’m happy to concede that across the entire possibility space, you could imagine a situation in which one route maximizes ridership but a slightly different version maximizes economic development goals or equity goals or environmental goals. But those divergences would in practice be either pretty rare or pretty small.

No, this is not an imaginary situation, and the divergences aren’t always small.  In our recent work for Portland’s TriMet, the agency articulated twin goals of ridership and equity, which led to a network that provides low-ridership coverage, but only only in low-income and minority areas.  Obviously, low-income and minority people generate ridership all over the network, so ridership and equity goals overlap more than they differ, but they still do differ significantly.

There’s a long-term, high-altitude view where Yglesias is right.  High-ridership services tend to create positive feedback loops with urban development that encourage even more ridership.  Smarter development could also reduce the need for coverage services over time.

But that’s not the altitude and timescale where most transit decision-making gets done, especially in service planning.  Those decisions are made by local elected officials or their appointees.  The problem is not just that people are yelling at them to defend their bus stop, although they are.  It’s that on a policy level, it’s just not always true that the high ridership network is the high-equity network.  That means that hard decisions have to happen.  I’m there to help boards reach those decisions, not give them the answer.

Induced Demand: An Axiom of Biology

Figuring out the relationship between this tweet and this article is left as an exercise for the reader.

Induced demand is the observed fact that if you make something easier to do, people will do it more.  For example, if you create new capacity for cars in a place where travel demand is high, the result is more cars.  If you build more capacity to “fix congestion”, you end up back near the same level of congestion you had before.

After decades of observing this pattern, most people are still reluctant to face what this means.  Part of the problem is that we’re presenting induced demand as an observed discovery, which allows us to quarrel over data, research methods etc.

But induced demand isn’t just an observed fact.  It’s also an axiom of biology.  We are as sure about it as we are of the facts of math.  This means we don’t really need to be doing this experiment over and over, just as we don’t need to keep measuring circles to be sure of the value of pi.

In this context an axiom is a statement that can be taken as true because it is part of the definition of a concept you are using, or follows logically from that definition.  The value of pi is axiomatic because it follows from the definition of a circle, in standard Euclidean space that describes our everyday world.

Now consider the concept of an organism.  It implies that:

  • The thing consumes some resource from its environment, in order to have enough energy.
  • It will expend energy getting this resource.
  • Therefore, it must run a positive balance sheet: The energy it spends getting the resource must be less than the energy the resource will provide.

We humans are organisms, so we do what they do.  In particular:

  • To have enough energy, we seek resources.  Money is a symbolic resource in this sense.  We also have other needs like shelter and security that also require resources.
  • We need to get these things in way that minimizes energy costs.  This is what I mean by easy.

We are mobile creatures, rather than barnacles or oysters, so this pursuit of resources often requires traveling. This means that time is also part of this basic calculation that determines survival.  The time spent pursuing a resource can’t be spent pursuing other resources, or doing other necessary things like sleeping.  So we must minimize our costs in both energy (which includes money) and time, while gaining as much energy (money) as possible.

From this it follows that people will tend to travel in ways that maximize their access to resources while minimizing energy cost (time and money) and danger.  People don’t always do this exactly, but the underlying biological imperative is unavoidable.

This means that:

  • If driving suddenly becomes easier (lower time and energy cost) than taking transit, more people will shift to driving, increasing congestion.  This is why road widening in high-demand places tend to lead to more traffic.
  • If a road widening makes it possible for developers to save money (i.e. energy) by building in more distant places where land is cheaper, they will do that.
  • This process changes the shape of the urban area so that people travel longer distances (due to sprawl) at slower speeds (due to congestion).
  • Therefore the average organism will need to expend more time and energy to reach the same resources it reached before.  (Your job flees from downtown to a distant business park where taxes are lower.  Your grocery store closes because a WalMart opened two miles away where you can’t walk to it, or even walk from the nearest point that a bus could get to.)  The organism will also be exposed to more danger as a result.
  • On average, organisms in this system end up in a weakened state, with a worse balance sheet of energy expended vs energy gained.

The organisms in this story are all trying to harvest more energy than they spend in the act of harvesting.   Even unimaginable aliens on distant planets would do this in the same situation.  So it’s axiomatic that, in the absence of other pressures, road widening in a high-demand area will induce more traffic and more sprawl.

So although road-building departments keep doing the induced demand experiment many times every year, and getting the same results, you don’t need to do more experiments, just as you don’t need to keep measuring circles to be sure of the value of pi.  You can add complexity by taking this into the human sciences and trying to model subtleties of human behavior, but all the resulting insights will be marginal compared to the axiomatic fact that above all, we’re organisms, so we’ll do what organisms do.

Access or Prediction? A Conversation with Alex Karner (and Willem Klumpenhouwer)

Alex Karner

Recently, I asked whether we should build transit infrastructure projects with the goal of expanding access to opportunity, as opposed to existing measures of success that depend on ridership prediction.  (If you’re not sure of what I mean by access, read this first.)  This stimulated a great conversation in the comments with Alex Karner, an Assistant Professor of Architecture at the University of Texas, Austin, with a useful interjection from Willem Klumpenhouwer, a postdoctoral fellow at the University of Toronto Transportation Research Institute.  It’s very lightly edited.

Here is the part of my piece that set this off, followed by our exchange:

[Most Federal criteria for transit funding] are built on the same shaky foundation: a prediction of ridership well into the future.  Access analysis may help to shore up those foundations, because an access calculation is much more certain than a prediction.

That should be especially obvious during the Covid-19 pandemic.  The utterly unpredicted ridership trends of 2020 are just an extreme example of the kind of unpredictability that we must learn to accept as normal. As I argued in the Journal of Public Transportation, we can’t possibly know with certainty what urban transportation will be like in 10-20 years, or how our cities will function, or what goals and values will animate people’s lives.

Ridership prediction models generally begin with something like an assessment of access.  If a project improves travel time for a lot of possible trips, that’s the starting point for a high ridership prediction.  But then, predictive modeling mixes in a bunch of emotional factors that amount to assuming that how humans have behaved in the recent past tells us how they will behave in the future.  This is equivalent to telling your children that “when you’re my age, I know you’ll behave exactly the way I do.”

Of course some human behavior is predictable.  We’ll still need to eat.  But the world is changing in non-linear ways, which means that the recent past is becoming less reliable as a guide to the future.  So if we measured access, we’d still be measuring ridership potential, but without all the uncertainty that comes from extrapolating about human behavior, or telling people that you know how they’ll behave 20 years from now.

Alex:

I agree with your criticisms of long-range forecasting but think there’s a substantial role for near-term (current year or opening-day) forecasts when thinking about the impacts of a proposed service change or the inequities inherent in the current system. Because these rely on more timely data about travel behavior, land use, and levels of service, we have more confidence that their results are meaningful. These forecasts can provide information about how travel times (walk, wait, in vehicle, and transfer), number of transfers, and out-of-pocket costs change or differ across people and places. (E.g., the proposed service change will increase origin-destination travel times for low-income transit riders on average by 8 minutes).

To be sure, accessibility (access/freedom) is super important. But we should also look simultaneously at expected impacts on transit riders today. Activists and advocates always request these types of measures when service changes are being proposed.

Willem Klumpenhouwer

Willem Klumpenhouwer:

Access is undoubtedly an important measure, and is definitely under-used as a metric of success or value in many transit system evaluations.

I do have one quibble with your argument, however. Measuring access now and using it for long-term projects into the future is *still* making static assumptions about human behaviour (that the destinations you measure access to are important and will be into the future), as well as assumptions about future land use. While I do think it’s not as explicitly modeled as with a standard econometric behavioral model, it’s still implied.

One way to potentially fuse some of that together and add flexibility is to get into the habit of bundling destinations into a weighted “basket of destinations”, something I argued in a JTG paper. Then the trick becomes figuring out ways to determine what those bundles should be.

Ultimately, I think there needs to be more research done on how access translates into use (of which ridership is one metric), and how that happens.

Jarrett:

Alex and Willem

Alex: I agree completely that there’s role for understanding current needs and maybe even near-term forecasting, but the kind of transit infrastructure we’re talking about here has to be useful for decades if not centuries, and the present is just too brief a time to be the the only consideration or even the main one. Since the narcissism of the present will dominate the project politics anyway, I want to highlight measures that push against the present bias, because there’s literally no other way to give our unborn grandchildren a place at the table.

We all live inside our grandparents’ bad infrastructure design decisions — decisions that made sense at the time, in the culture of the time, for the people who were being listened to at the time. You can work to make that present-oriented conversation smarter, more fact-based, and more inclusive/equitable, and I support that 100%, but your approach still leaves us saying that our grandchildren will be just like us in all kinds of ways that we have no right to assume.

How do we know what our grandchildren will want? Two ways: (1) We can assume that they will want what history and biology tell us that humans have always wanted and (2) beyond that, we can focus on giving them the freedom to be whoever they turn out to be and want whatever they turn out to want.

For example, under (1) we have the biological needs that drive a lot of our daily activity, but also historical insights like Marchetti’s Constant, which help us set useful travel time budgets for a daily trip or “commute.” We can do some philosophical work to delineate the boundary of those two categories. This is where I was going with the Bortworld thought experiment in my Journal of Public Transportation paper.

Willem raises a good point about how we can know, on behalf of our grandchildren, what the relative importance of different kinds of destinations will be. Biological and historical knowledge can take us a long way.  When it comes to human motivations, the longer something’s been true in the past, the more likely it is to be true in the future. Finally, yes, that weighting will still be a judgment. But if we could get to the point where we were arguing mainly about that, I think we’d have made transformative progress in how we think about infrastructure. More on that here soon.

Alex:

I think Willem’s point about having to make assumptions about future land use–either how it changes or assuming it stays constant–clarifies that accessibility or freedom analyses are still subject to at least some of the limitations of long-range ridership forecasts.

In terms of infrastructure, I’m fine with having different standards for fixed-guideway projects with high capital costs and longer-lasting impacts on urban form as compared to bus network redesigns or other tweaks to the bus network. Although I wonder how much land use and density is already baked in and how that differs by urban areas. Will the locations of high land use intensity look much different in 50-75 years, in terms of their locations, than they do today? If not, then holding land use constant and also using current/near-term forecasting can both provide important insights about impacts now and in the future. I don’t think we have to pick one set of metrics or approaches over the other. Both are important.

One key area where I think we differ is in our relative weighting of future vs. past impacts. I definitely appreciate your future orientation–this is important from a climate, health, sustainability and resilience perspective. But I think to make traction on these issues and to get residents to buy into any specific public transit vision, we (academics, practitioners) have to acknowledge that transportation infrastructure development (highways *and* transit) has historically had baleful effects on low-income people and people of color in the US. Black people were especially negatively affected throughout the 20th century and continue to bear the brunt of many of the transportation system’s most direct impacts while not sharing fairly in the system’s benefits.

I see looking at impacts on current riders and near-term forecasting as at least partially atoning–or at least acknowledging–these historical impacts. In conducting a current/near-term analysis, we’re saying that we value the experiences of current public transit riders and want to understand how our proposed changes will affect them. To be sure, there’s a lot more than can and needs to be done in this regard (this pending TCRP project will help to suss out exactly what a reparative approach for public transit planning/policy could look like). But jumping straight to the future without acknowledging the past seems like a surefire way to alienate the essential riders upon which public transit depends.

The folks at the Untokening Collective have written about this in their “Principles of Mobility Justice,” one of which is the following: “Mobility Justice demands that we fully excavate, recognize, and reconcile the historical and current injustices experienced by communities — with impacted communities given space and resources to envision and implement planning models and political advocacy on streets and mobility that actively work to address [the] historical and current injustices [they experience].”

Current/near-term forecasting doesn’t live up to this high standard on its own, but providing resources to communities to vision future transportation systems and to understand how their travel outcomes (in terms of performance, not necessarily choices) will differ in those futures might get us moving in the right direction.

Jarrett:

We are in complete agreement about the need to show the impacts of proposals on the present, especially relatively short term work like bus network design. That’s what we do in all our projects.

Access analysis honors the future but is also an important way to talk about the present. For example, we can talk about the impact of a service change on the access to opportunity of existing riders based on their boarding location, so that we are specifically addressing the benefits and disbenefits that each such rider will experience. This can help riders see beyond an understandable initial assumption that all change is going to be bad for them.

There’s also a space for access analysis in giving elected officials another way to think about what they are hearing from the public, and to relate a service plan debate to larger goals that they care about, because expanding access supports so many of those goals.

But you’ll have to explain how forecasting serves the goal of “excavating … historical and current injustices.” How does predicting human behavior the near future help us understand the past, or our moral options for rectifying the injustices of the past? That one I just can’t follow.

Alex:

It seems like we also differ in terms of whether we think access analyses are enough on their own to demonstrate present-day impacts. The analysis you describe based on boarding location sounds helpful. I’m arguing that in addition to evaluating those quantities, we should also look at impacts on *current trips* and *current riders,* summarized by place or for specific groups (e.g., low-income people, Black people, equity-priority neighborhoods, etc.). Access it great, but it does not tell us how people are using the system today and how a proposed change will affect the trips they currently need to undertake.

Our knowledge about the injustices of the past informs the places and groups that we think it important to analyze. A high-quality transit rider survey will capture the travel behavior of a sample of transit riders. These results need to be carefully weighted and expanded to represent all transit travel. This weighted and expanded sample is our best representation of the full range of travel being undertaken on a particular system. Trip characteristics can be modeled to assess how they change from a base (no-build) to a build scenario. These changes represent the real impacts that will be experienced by actual travelers today and can be used to understand differences between groups. If done well, this analysis will provide insight into current injustices, if any exist (e.g., wide disparities between the trip characteristics between places or groups).

If desired, appropriately crafted simulation models can also be used to understand how behavior will change in response to changing levels of service (or demographics or land uses). Model results can also be used to assess current injustices and to help us understand whether we are making progress towards redressing historical wrongs.

Jarrett:

We certainly don’t disagree about the value of studying how the system is being used now, and evaluating impacts of changes on existing riders. We see the value in using rider surveys for this purpose, alongside access analyses that show how a network proposal changes what people *could* do (but aren’t doing now because the transit system doesn’t let them).

But I’m still puzzled about how models that predict “how behavior will change” are helpful in understanding or rectifying past injustice — unless you just mean really safe predictions such as “if we make high-demand trips possible that aren’t possible now, people will begin making those trips.” Is that all you mean?

Alex:

That’s not all that I mean. If we have a “good” rider survey collected recently we can use that survey to estimate a ridership model that will help us understand how changes in level of service and land use will affect transit use. The changes need not be limited to “high-demand trips.”

If we constrain our forecasts to use near-term or current year data, then we will have more confidence in the outputs we’re generating than if we use a 30- or 50-year horizon.

And if we examine outcomes for groups that have historically experienced injustice, our results can speak to how their experience of using public transit will change.

We seem to end where we began, Alex is arguing that to understand people’s experience, we have to predict what they’ll do.  And I’m wondering if it’s better to just talk about what they’re free to do.  We debate, you decide.

Racial Justice and Transport Modeling

Two important thinkpieces just appeared that seem to be about different topics but should to be read together.

Christof Spieler, the Houston METRO Board member who drove the 2015 network redesign at the political level, has a piece at Kinder Institute called “Racism has shaped public transit, and it’s riddled with inequities.”  Meanwhile, in Vice, Aaron Gordon takes on “The Broken Algorithm that Poisoned American Transportation,” by which me means transportation demand models.

Spieler outlines how transportation, like everything else, has been forged through many decisions that reflected the values of the time, and how this history has created structures that still produce racially unjust outcomes today.  These structures can be literal infrastructure — like bus lanes designed to be useful for suburban commuters but useless for buses linking inner city residents to opportunity — but they can also be a wide range of bureaucratic and analytic procedures that continue those racially unjust practices in more subtle ways that the people executing those procedures don’t have to notice.

One of those procedures is transportation demand modeling, as Gordon describes it.  The best modeling is not nearly as dumb as the examples Gordon highlights.  But the problem of all modeling is that to show the effects of a proposed action, you have to assume that everything else in the background will remain constant, or at least will continue changing only along predictable paths.

When the modeling process considers many possible futures, the one that is most like the past is called the conservative assumption, as if that means “this is the safest thing to assume.”  This assumption seems calm and rational, attracting many people who would never call themselves conservative politically.  But fact, assuming that the future will be like the past can be crazy if the trajectory defined by the past is unsustainable — environmentally, financially, or morally.  “Unsustainable” means that it is going to change, and in that case, the “conservative” assumption is really the “self-delusion” assumption.

Transport modeling can’t be thrown out, but it never tells us what to do.  It is a basic logical fallacy to say that “the modeling shows we must do x.”  All modeling insights are if-then statements.  A full version of this statement, which I would like to see at the beginning of every modeling-drive transportation study, is:  “This report shows that if the future matches our assumptions, then you can expect this outcome.  But the future may not be like that.  In fact, maybe it shouldn’t be like that.  So what really happens is up to you.”

US Congress Considering Freedom-Based Measures of Project Success

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!

How Can We Study Things in Isolation? They’re Connected!

Whenever I present a bus network redesign plan, I’m always accused of ignoring important things.  How can I design a bus network, people say, without also planning for bus lanes, or bicycle parking, or road pricing, or parking policy, or urban structure? These things are all connected, they say!

Yes, they are all connected. But despite being connected, many planning tasks are separable:

  • Two projects are connected if they affect each other’s outcomes. For example, a network redesign and a bus lane project will certainly improve each other’s benefits over what either could do alone.  A rail line and a bus line parallel to it are competitors that will undermine each other’s outcomes, so they are connected too.  (Deep ecologists would say that almost everything is connected in this sense.)
  • Two projects are separable if one can be done before the others, and will achieve some benefits  by itself, even while waiting for the other connected parts to happen.

I know why people get anxious about this, because we all see situations where things were separated that really were inseparable. A rail line and a freeway are built side by side, without noting how each will reduce the demand for the other.  Maybe bus routes are designed without thought to connections between them, or worse, great infrastructure for bus connections gets built in a place where it’s not actually useful to the bus service.  A public transit service ends at a political boundary even though the demand doesn’t end there.  These are all examples of projects being separated when they were not really separable.

On the other hand, no human brain can focus on everything at once.  If we tried to do bus network redesign, fleet modernization, bus lanes, bike parking, road pricing, and parking policy as part of one project, it would never get off the ground.  Just co-ordinating the hundreds of experts needed to deal with all dimensions of such a project would consume most of our effort.

More important, in any project, everything moves at the speed of the slowest element, which is why it so often takes forever to get things done.

So separating projects is the only way for anything to happen soon. We are not denying that everything is connected. We are saying we have to start somewhere, and make some progress, even as other pieces of the puzzle are in the works.

Like any plan, a good network redesign effort requires clear thinking about separability.  A redesign is mainly a revision of the patterns in which buses run, but this process always identifies infrastructure and policy changes that are also needed. Sometimes these are truly inseperable:  The specified number of buses can’t meet at point A unless the facility there is enlarged to have room for them.  If the plan requires people to change buses at an intersection, we need to make sure there’s shelter and safe street crossings, and so on.  If the fare structure is penalizing changing buses, that needs to be fixed if our plan wants to encourage that.

But we fight to make the list of inseparable things as short as possible, because every time we decide that something is inseperable from the plan, that becomes one more thing that could stop the whole plan if it hits some kind of snag.  We ask:  Would the redesign still be possible, and worth doing, if some infrastructure or policy element doesn’t get done?  Sometimes this leads to good tactical thinking:  Can we do this necessary interchange quickly on-street, even while waiting for the funding and consensus to do the permanent facility that’s really needed?  Can we make some patches to the fare system while the ultimate system is still being worked out?

Another test is:  Does doing Project A without Project B actually make things worse?  If not, this is another signal that the projects are probably separable. The answer, for bus network redesigns, is almost always no.  By itself, redesign will achieve significant improvement even as it leaves a lot of other frustrating problems in place.  But getting it done may make other improvements politically easier if the result is that public transit is more visible, more used, and thus more widely valued.

So when people respond to a network redesign proposal by being angry that it doesn’t talk about bike lanes, electric buses, or road pricing, they’re confusing connectedness with inseparability.  Our network redesign study isn’t ignorant of those things just because we’re not talking about them.  We’re just talking about something different, something that’s also important and needs some attention.  A good network redesign, if allowed to succeed, will make all those other things easier.  And in any case, the redesign itself is important enough, and hard enough to explain, that it deserves the public’s full attention for a few weeks.

Everything is connected, but many things are still separable.  That’s a good thing, because if they weren’t, nothing would get done.

“To Predict with Confidence, Plan for Freedom”

 

The Journal of Public Transportation has a special issue out consisting of thinkpieces by a range of figures in the business.  I’m honored to be there alongside industry leaders like Susan Shaheen of UC Berkeley, Graham Currie of Australia’s Monash University, Kari Watkins of Georgia Tech and Brian Taylor of UCLA, as well as our favorite operations and scheduling consultant, Dan Boyle.

My contribution is called “To Predict with Confidence, Plan for Freedom.”  It basically outlines the argument of my next book, so this would be a great time to hear some critiques of it.  Here’s the opening:

What will urban transportation be like in 10-20 years? How will automated vehicles interact with social and cultural trends to define the city of tomorrow? Will the vehicles of the future be owned or shared? How will pricing evolve to motivate behavior? What will happen to public mass transit? What other innovations can we expect that will transform the landscape? This paper, which is merely the outline of a larger argument, suggests three interconnected answers.

  • We can’t possibly know. History has always been unpredictable, punctuated with shocks, but if the pace of change is accelerating, then unpredictability may be increasing too.
  • We can reach many strong conclusions without knowing. A surprising number of facts about transportation, including some fairly counterintuitive insights that would be transformative if widely understood, can be described and justified solidly with little or no empirical ground, because they are matters of geometry and physics or of nearly axiomatic principles of biology.
  • Prediction may not be what matters anyway. If we abandoned hope of predicting the future, we could still describe a compelling outcome of transportation investment, one that motivates many people who will never care about a ridership prediction or economic impact analysis. We could also predict it in the sense that we can predict the continued value of pi. That idea is freedom, as transportation expands or reduces it.

So if that catches your interest, read the whole thing, and share your comments below!

Learning from Portland’s “For Rent” Signs

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Photo: City Observatory

Joe Cortright spreads the good news that “For Rent” signs are proliferating across Portland, signaling an easing of the affordable housing crisis.  And he points out a critical thing that many activists miss.  That luxury housing that affordability advocates decry does improve affordability for everyone.

The … myth is that you can’t make housing affordable by building more of it, particularly if new units are more expensive than existing ones. The surge in vacancies in existing apartments is an indication of the interconnectedness of apartment supply, and an illustration of how construction of new high end, market-rate units lessens the price pressure on the existing housing stock. When you don’t build lots of new apartments, the people who would otherwise rent them bid up the price of existing apartments. The reverse is also true: every household that moves into a new apartment is one fewer household competing for the stock of existing apartments. This is why, as we’ve argued, building more “luxury” apartments helps with affordability.  As our colleagues at the Sightline Institute recently observed, you can build your way to affordable housing. In fact, building more supply is the only effective way to reduce the pressure that is driving up rents.  (Emphasis added.)

Why mention this on a transit blog?  Because the mistake activists make here is the same one that many transit advocates make, which is to think of wealth as a set of boxes, called classes, that never intermix or affect each other.  It’s the same mistake that underlies the false dichotomy of “choice” and “dependent” riders in transit planning, the notion that you need separate services for each type of rider because they are absolutely different kinds of people who will never mix.

In fact, wealth is a spectrum.  People are everywhere along it.  Admittedly, this is less true that it once was, but it’s still true.  So although people certainly differ in wealth and thus in the options they have, they are still part of the same diverse market — for housing, as for transit.  When advocating for a fairer and more equal economic world, don’t lose track of this.  Don’t become so focused on us-them differences that you miss the solution that improves things for everyone, including you.

 

 

Best Ever Podcast Interview of Me

invisible city logoIn her spare time, Toronto Chief Planner Jennifer Keesmaat hosts a podcast series called Invisible City.  Her hour-long sessions go deeply into a
n interesting urbanist topic, and recently she did an interview of me.  We were both having great fun, and it turned into the best long-form interview that I’ve done.  (This 2012 Colin Marshall interview — which is more personal and where my ideas were much less clearly formed, is the only one that comes close.)

Jennifer skillfully provoked a discussion that requires no geekery to follow.  You can share it with your friends who have only the vaguest notion of what transit is, and many, I think, will still enjoy it.  There are a few
Toronto references, but nothing that will baffle a reader from elsewhere.

It’s here.  Hope you enjoy.