Some Doubts about Access Analysis

Click to enlarge: The basic idea of access.

Access is your ability to go places so that you can do things.  In this “basics” article, I laid out why I think measuring access would help advance many important goals that appear to be in conflict, and I suggested, for both practical and moral reasons, that public policy should care about what people can do — i.e. their freedom — as opposed to just what we computer-enhanced elites predict people will do.

Many smart people have offered critiques of this idea, or at least of its practical applications.  I’m particularly grateful to Alex Karner of UT Austin and Willem Klumpenhouwer of University of Toronto for this conversation, and to Matt Laquidara, who laid out a very thoughtful critique early on.  Please point me to others that I may not have seen.

Two Kinds of Critique

First, let’s distinguish between rhetorical and investigative uses of analysis.  In my practice as a consultant, I’m trying to break through into a public conversation, and I’ll do this only with simple explanations of things that obviously matter to people.  It’s not wrong for me to oversimplify to make the idea visible and convey its importance.  The work can be accurate, as far as it goes, and still be simplified.

So there are two kinds of objections to my thesis:

  • those that undermine the fundamental claims of access analysis and
  • those that add nuance that could make access analyses more accurate, precise, and/or more relevant in edge cases.

The latter, of course, are not objections at all.  They’re just avenues for further development.  You’ll see a lot of these throughout this post.

My claims for access analysis

My argument for access analysis is here, but let me quickly list the aspects of my position that seem adjacent to the critiques, and thus most relevant to this response:

  • To the extent that we make strong predictions about what humans will do in the future and what outcomes will result, we are assuming that people are not really free.  Free people will surprise us.  Prediction also appeals to a human desire for control over history that is just not realistic.  The future really is unpredictable.  (More on this in my Journal of Public Transportation paper here.)
  • There are degrees of prediction and the best predictive work makes much softer claims.  Prediction of only near-term events, or prediction that speaks only of ranges of probability, is less problematic.
  • All analysis is more reliable when it predicts that people will continue to be what they’ve always been throughout history and across cultures.  It’s much more problematic assert the permanence of aspects of human society found only in the present, or in the very recent past, or in only one culture (however dominant that culture may be).  Again, this is less of an issue for shorter-term predictions.
  • Access analysis doesn’t need to be perfect or free of questionable assumptions. It just needs to be much more reliable than predictive modeling.  Even if (hypothetically) the two methods turned out to be equal on this score, access analysis would still be preferable because:
    • It’s about something that everyone cares about.
    • It is correlated to many outcomes that we urgently need our transport system to deliver.
    • It is a much more transparent process where the assumptions and their impacts are easy to document, even if they’re controversial.
  • When you pile up the assumptions on both sides, access analysis carries a much higher degree of certainty because it isolates geometric, physical, and biological insights and relies on them to the greatest extent possible.

So let’s look at the biggest doubts about access analysis.

Is it good only for commute trips?

Our firm‘s analyses usually focus on trips to work or school, and people routinely object that those aren’t the only kinds of trips.  Of course they aren’t.  They aren’t even half of all trips.

However, when we think about the most long-term freedoms we need, the freedom to construct our lives and commitments according to our values, the commute (work and school) looms large.  Your ability to hold a certain job, or study at a certain school, will do a great deal to define the capabilities you’ll develop, the money you’ll earn, the social networks you’ll be part of, and so on.  Those things, in turn, will create the conditions for the freedom or unfreedom that you’ll experience down the line.  So when we seek to quantify freedom in the broadest sense, it may be reasonable to put special emphasis on access to work or school.

Commutes are round trips made on a majority of days and that include spending several hours at the destination. They are almost always to work or school.  Commutes are easier to analyze than other trips because:

  • It’s easy to calculate how many people will value a trip to each destination.  While the number of people who want to go to a store will vary with the quality of the store, its competition, and people’s attitudes to it, every job or school enrollment position will be the destination of exactly one resident.
  • Data about the location and quantity of jobs and school enrollments are relatively good in developed countries, although there’s still a lot of variation.
  • We have a useful rule of thumb about the tolerable travel time for commutes: Marchetti’s constant, the observation that across many historical periods, people have tolerated a one-way commute time of about 30 minutes.  This is an example of the principle that if an aspect of human culture been true far into the past and across many cultures, it’s a more reliable basis for positing what freedoms people will continue to value.

Can we look beyond commutes?

But is access analysis good only for commutes?

In our work we do extend the principle to other kinds of trips.  In our recent San Francisco work, for example, we calculated access to groceries, low-cost food resources, parks, pharmacies, and medical centers.   We have also experimented with more precise pairing of residents and destinations.  For example, if we have good data on both income and wages, we can calculate low-income people’s access to low-wage jobs.  We can also exclude retired people from the database of people who value the freedom to access work or school opportunities, but include them — or even make specialized calculations for them — when looking at other destinations that tend to matter in a retired person’s life, including groceries, medical, and parks.

When we move beyond the commute, however, the three benefits I listed above are all absent.

  • We cannot calculate, for a given person, how much freedom is provided by the ability to go to one park or medical center over another.   The tool would be highly reliable for identical destinations, like McDonalds restaurants or whatever, but I think we’d all agree that if you can get to three McDonalds restaurants you don’t really have three times the freedom that comes from being able to get to just one.  The freedom value of alternative destinations depends precisely on them being different from another, and we have no hope of abstractly quantifying that value.  In San Francisco we inevitably made simplifying assumptions: valuing parks by the acre, for example, and valuing all medical centers the same.  For present-oriented analysis you can dig deeper into trip generation patterns, through surveys etc, and refine assumptions, but that works only for analyses meant to be relevant only in the present.  This is a genuine weak point for analysis.
  • We have lousy data about most nonwork and nonschool destinations.  Some of these things change rapidly.  Even if we know where they are we usually don’t know their size or intensity.
  • It’s harder to assign an acceptable travel time budget for a nonwork and nonschool trip, as I’ll address below, although we can still make educated guesses.

But predictive modeling has all these problems too!  Most such modeling relies too heavily on the commute as the primary trip that matters (and on rush hour as the primary time of day that matters).  All of the problems of the non-work trip are at best equal for predictive modeling as for access analysis.

Arbitrariness of Time Budgets

When I explain access, I have to start with the isochrone (see image above), the area that a person at a certain location could reach in a fixed amount of time.  Thus, in the access analyses that underlie our reports, we usually describe what area could be reached in 30 minute or 45 minutes.

Why 30 and 45 minutes?  If we had twelve fingers I’d probably be using 36 and 48.

There are two problems here: (1)  We are imposing an obviously arbitrary threshold, valuing a trip that can be made in 29 minutes but not 31, and (2) We are asserting an amount of time that people find acceptable, which requires an explanation.  These are interconnected.

How do we know what travel times people tolerate?

Everybody has the same amount of time.  There are 24 hours in everyone’s day.  When we perceive a travel time as acceptable it’s because it’s an acceptable percentage of the total time available.

You could argue that the perception of time is different in culturally “slow-paced” as opposed to “fast-paced” places, as in the stereotypes of New Orleans and New York, respectively.  On the other hand, setting travel time budgets differently based on the dominant culture of a place is itself oppressive, as more and more people live in places where theirs is not the dominant culture.

Meanwhile, economists like to talk about “value of time,” which is about the value of your time to the economy, not to you.  That’s definitely not what we should care about here.  We’re talking about an equal right to freedom here, and the only way to do that is to posit an equal value of time.

We can plunge into social science research at this point, looking for non-commute equivalents of Marchetti’s constant.  How long do people spend going to the grocery store?  How long do they spend going to a park?  The data will be all over the place, and it will be hard to separate how long people are willing to spend from how long they are forced to spend given their situation.  Again, if we can find something that’s been true longer, and over more cultures, we should rely on it more.

But I think we could start with a couple of principles, which I suspect are relatively transcultural and transhistorical:

  • We are willing to spend longer traveling if we will spend more time at the destination.
  • We are willing to spend longer making a trip we make less often.

We have a finite amount of time in our day, so if we have many commitments, we’ll need to hold down the total percentage of our day spent in travel.  So the commute is likely to be the longest trip we’ll make in a typical day, though we may make longer trips less often.  Errand trips, lunch trips etc. are likely to need to be shorter than commute trips.

For retired people, diverse errand trips (medical, recreation, shopping) may be able to take longer than for people who spend much of each day at work or school.  We need more research about retired people (and other people who are not in school and don’t have jobs) because their tolerable travel time may depend on the fact that their daily time is less scarce, and that some time-saving actions, like walking further to a more frequent bus stop, carry higher disincentives for them.

I think these principles, buttressed by some research, could help us creep toward some reasonable travel time budgets:  Marchetti’s constant (30 minutes one way) for commutes, a lower number for typical errands, but possibly a higher number for retired people.  Is this all wildly imprecise?  Yes.  Is it arbitrary?  No, we’re not picking numbers out of the air.  We have a sense of the right ranges.  Now we come to the next problem:  While the roughly correct travel time budget is not totally arbitrary, the exact one we use definitely is.

Why 30 minutes?  Why not 31?

From, our work for Portland Enhanced Transit Corridors project: A person at 82nd & Foster has lost 19% of their 45-minute access to jobs in a decade (2009-19) due to declining bus speeds.

Access analysis starts with an isochrone showing where someone could get to in a fixed amount of time, such as 30 minutes of 45 minutes.  But as Matt Laquidara points out, “no one who is willing to take a 45 minute trip is going to consider a destination 46 minutes away totally unreachable.” In a footnote he adds: “Why bound time at all? In theory, it’s possible to have no maximum time and compute the trip duration for every origin, destination, and starting time combination. Those could be aggregated into an average or percentiles.”

Yes, if you could tolerate a given travel time, you could probably tolerate one that’s a minute longer, but you’ll have limits.  In growing cities, city bus lines in mixed traffic often slow down very gradually, a classic “boiling frog” event that causes big cumulative damage but never generates a single crisis that would attract attention and action.  To a great extent, people who are used to a 45 minute bus ride may accept that it’s 46 the next year and 47 the year after that.

But at some point, they will run out of time in their day.  The person whose 45-minute ride is now 55 minutes will eventually give up.  They’ll change modes, or quit that job, or do what’s necessary to keep their total daily travel time down.  Meanwhile, a new customer who looks up that commute will see a 55 minute travel time, and say no thanks.

So a minute’s difference may not matter, but a 10 minute difference probably does.   And to talk about access as freedom, we need to be very approximately right in the travel time budget.  Perhaps we’ll get closer if we come up with bell curve of weighted travel time budgets for commutes, maybe peaking at 30 minutes one way but with a long tail stretching upward past 45.  This is a reasonable solution to the problem of assigning too much significance to a one-minute difference.  But if we get too fancy about how we draw the curve, it takes us back to the same problem.   It’s easy to quantify what people are putting up with in terrible situations, but that’s different from what a free person would tolerate.  We aren’t describing people’s freedom if we’re relying on data about their unfreedom now.

So some arbitrariness, proudly proclaimed, may be better.  For my own rhetorical purposes in presenting and justifying transit service plans, the soundbite and picture take us far:  “The average Dubliner can get to 20% more jobs and school enrollments in 30 minutes, and here, let us show how the 30-minute wall around your life changes.”  People who hear me say that rarely accuse me of claiming that 30 minutes is radically different from 31.  They know I’m making a simplifying assumption so that I can show them something that they can understand, and whose value is obvious to them.

Perils of Aggregation

It’s one thing to analyze all the various kinds of destinations.  It’s another more perilous thing to decide how these should be weighed to create a single measure of access.  As Matt Laquidara writes:

I’m deeply uncomfortable with most any determination of what locations are important, and consequently, which ones are not. I don’t want to do it myself. I don’t want anyone else deciding it either.

For reasons we explored above, there are always going to be trip desires that are just too scattered, and for which there’s so little data, that they will tend to be omitted in analysis.  Residence-to-residence trips are probably one example.

There will also always be the problem that some destinations are hard to quantify.  In San Francisco, we assumed that every acre of park was equally valuable in terms of people valuing the freedom to reach it, but of course there are lots of ways to question that, and to introduce other factors such as park infrastructure.  Each of those factors would make the measure more precise but also more questionable in terms of how it was projecting some people’s preferences (those who yell loudest at meetings, for example) onto the entire population.

But let’s say that refinements to access analysis make it possible to cover about 95% of trips — or as access analysis would describe it, 95% of the destinations that people will value the freedom to reach.  Matt’s objection arises only when we aggregate these different destinations into a single access score.  If we declare that one acre of park is worth 0.26 pharmacies, that’s a value judgment.  We could try to apply survey data about how much demand each place attracts, which requires assuming that people are making all the trips they want to make.  Or we could just stop trying to aggregate, which I prefer.  The elected and public audiences with whom I speak usually want to hear separately about each destination type, because each is the basis for a different kind of story and has a nexus with different kinds of public policy.  If you care about food security, look at access to groceries.  If you care about how much exercise people get, look at access to parks.  And so on.

To sum up

  • Access analysis is not perfect but can be more reliable than predictive analysis, if only because it makes a more modest claim.
  • Predictive modeling requires all the assumptions that access analysis requires, but adds even more assumptions about how human behavior in the future will resemble that in the recent past.  Access analysis does not need to include such perilous assumptions.
  • We can describe access for commutes with relative confidence.  Commutes are a minority of trips but there are a variety of reasons to consider them important.
  • Non-commute trips are important but harder to analyze.  Still, there’s a basis for making some reasonable assumptions.
  • Further work is needed on how to think about freedom of retired people, and more generally about how people’s tolerance for travel time varies with the competing demands on their time.  Up to now I’ve been using busy people as the primary frame of reference.  This probably contains a bias: I want transit to be useful to busy people, not just to people who enough time that they don’t feel constrained by slow service.  Most people are busy.

This post is out there to start arguments, though I hope it also resolves a few.  I am not an academic scholar, but I do feel confident in what I asserted in the “my claims” section above, at least until I read the comments, as you certainly should.  Then, I may add some updates here.

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.


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.


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.


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.


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.


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.


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?


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.

What Should the Criteria for US Federal Transit Funding Be? (They’re Asking You, Now!)

Should proposed public transit infrastructure in the US be judged on whether it helps people go places so that they can do things?  The US Federal Transit Administration (FTA) is asking this question right now.

FTA helps fund most major transit construction projects in the US.  Recently, these programs have doled out about $2.3 billion per year in capital funding for transit projects across the country. The Senate Infrastructure Bill would nearly double the annual funding for these programs for the next five years.  If there’s a piece of transit infrastructure you want to see, or one that you oppose, you should care about how the FTA makes its funding decisions.

Congress has defined the criteria that FTA must use to evaluate the projects. But the FTA has broad discretion in deciding how to define the measures for each criterion. So now they are asking you, me, and everyone about how we ought to change or update those measures.

Their questions should make us optimistic about what US transit funding could become.  They don’t sound like an ancient bureaucracy going through the motions of public consultation.  Instead, the agency really seems to want our opinion about how they should measure the success of their investments, a decision that will directly determine what gets funded and built.  Read the questions yourself if you don’t believe me.

Does it matter if we can go places, so that we can do things?

FTA asks many good questions, but one especially stands out.

Should FTA consider ‘‘access to opportunity’’ under the Land Use criterion? If so, how specifically could FTA measure it? For example, should access provided by the project to education facilities, health care facilities, or food stores be considered? Please identify measures/data sources that would be readily available nationwide without requiring an undue burden on project sponsors to gather and FTA to verify the information.

Access is your ability to go places so that you can do things in a reasonable amount of time.  Access reframes discussions of travel time:  Instead of asking how long it takes to go to a particular place, you look at how many useful places you can go in a given time.  In short, we’re talking about access to opportunity, which means not just work or school but your freedom to do anything that requires leaving home.

If you’re not familiar with the concept, please see my full explainer here.  But the most important point is that when we increase people’s ability to reach destinations in a shorter amount of time, we are improving ridership potential, revenue potential, climate emission benefits, congestion mitigation benefits, overall access to opportunity, and personal freedom, and we can also measure whether we’re doing these things equitably.  Access measurement can help meet all of these seemingly disparate goals.

Access and the Land Use Criterion

When the FTA asks about whether access matters, they are thinking about this in the context of their Land Use criterion.  They deserve an answer on this, although they also should hear about how caring about access would affect other criteria they care about, which I’ll touch on further below.

FTA’s Land Use criterion measures how much population and employment is around the stops or stations of a proposed project. The point is to determine that there is enough demand adjacent to proposed facilities.   (The criterion is not about the ability to generate future development – that’s under a different criterion, Economic Development.)

This table, from the FAST Updated Interim Policy Guidance dated June 2016, gives you a sense of how this evaulation works now:

Federal Transit Administration, Final Interim Policy Guidance Federal Transit Administration Capital Investment Grant Program, June 2016. p 15.

A project gets a higher rating if there’s more density around the station, and also if there’s more employment anywhere on the “system”.

But what do they mean by “the system”?  Here’s the crucial footnote:

The total employment served includes employment along the entire line on which a no-transfer ride from the proposed project’s stations can be reached.

So all destinations that require a connection are excluded, while all destinations on the same line, even if they are an hour away, are included.  In other words, as long as you get to stay in your seat, it doesn’t matter how much of your life you spend commuting.  By contrast, if you can get to lots of jobs quickly with a fast transfer, those jobs don’t count in assessing the value of the line.  Travel time, and hence access, don’t matter at all!

If you have an hour and 40 minutes to spare, you can go from Gresham to Hillsboro without leaving your seat!  But should that count as access?  Source: Trimet, Portland, OR.

For example, in Portland, where I live, a single light rail line will take you across the region, from Gresham to Hillsboro, in one hour and 40 minutes – far too long for a one-way commute.  But under the current method, all the jobs in Hillsboro would be counted as providing value to someone in Gresham, while the jobs that are less than an hour away – on a trip that requires the train and a bus – count for nothing.

So “Employment served by the system” is really just “Employment served by the line”  Likewise, the measure gives zero value to populations that are not at stations but that can get to stations easily via connecting buses.  In short, the measure excludes all the benefits of actual networks, which are a bunch of lines working together to expand where people could go.

How would an access metric change this approach?  Suppose the measure were something like “increase in the number of resident-job pairs that are connected by a travel time of 30 or 45 minutes.”  

A resident-job pair is an imagined link between every resident and every job (or school enrollment).  Each link represents a possible commute, which is an opportunity that someone might value, now or in the future.  The number of resident-job pairs in a region is the number of residents times the number of jobs (or school enrollments).  A very big number, but we have computers!

If we measured access in this way, what effect would it have on how FTA evaluate projects?

  • It would still quantify the benefit of land use intensification around stations. These areas tend to get the largest access improvement from a project, so that improvement, multiplied by the density of population and jobs, would generate a higher score.
  • It would measure what that density achieves for mobility. From a transportation perspective, the value of density around a line is that it provides the line’s benefits to more people, so that more people can get to more useful places sooner.  So maybe we should measure what we’re really talking about.
  • It would consider land use in the whole area that benefits from the project, not just around stations. It would reward communities that have thought about the total transit network more deeply and made some commitments about it.  The tendency to propose a line in isolation, without thinking about its role in a network, is a very common problem in US transit infrastructure.
  • It would refer to something that everyone cares about: their ability to go places so that they can do things.

What about equity?  The current criteria specifically measure the quantity of affordable housing near stations, and its likely permanence – an important tool to discourage displacement due to gentrification.  That measure definitely still matters.

But in addition, you could measure the access experienced by various racial or income groups, and make sure that this isn’t much worse what the entire population experiences.  For low-income people, you could look at their links to low-wage jobs and educational opportunities, so that it emphasize the commutes that they are most likely to need or want.  This would ensure that every element of the land use pattern is equitable in its most important aspect: the way that it ensures fast access to many opportunities.

Finally, FTA specifically asks whether access to “education facilities, health care facilities, or food stores be considered”.  The answer is surely yes, because most transit trips are not work trips.  We must measure access to all these things for populations likely to care about them, to the extent that the data permits.

For example, you could construct a database of all resident-grocery store pairs and run the same calculation, probably using a shorter travel time budget like 15 or 30 minutes.  You could do the same for healthcare.  You could construct a database linking school-age residents to school enrolments, and young adults to university and college enrolments.  Retired people could be excluded from the residents-jobs database but included in databases of, say, links from residents to healthcare, food, etc.  There are many ways to broaden the diversity of travel desires that a good network needs to serve.

The relative importance or weighting of all these measures would need more debating, possibly based on the size of each market in the region’s travel patterns with some bonus weighting for equity.

But to sum up:  When we talk about existing land use as a transportation criterion, what do we really mean?  I think we mean that the land use pattern contributes to a transit project’s ability to expand many people’s ability to get to many places in a reasonable amount of time.  So let’s measure that!

Access or Prediction?  A Broader Question for FTA

Land use is just one of the six criteria that FTA uses, and the one they have specifically asked about.  The others are:

  • Mobility Improvement
  • Cost Effectiveness
  • Environmental Benefits
  • Congestion Relief
  • Economic Development

Except for Economic Development, all of these 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.

Still, 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.

Here’s how the access concept could illuminate each of the FTA’s criteria:

For the Cost Effectiveness criterion, Congress has required that FTA measure the capital and operating cost of a project and divide that by the total number of trips (predicted by a model) to effectively measure the cost per trip. Since it would take an act of Congress to change this measure, it stands to reason that FTA should be looking to access measures as factors to use for other criteria. However, we should also assess projects based on the increased access provided per dollar expended.

For the Congestion Relief criterion, FTA measures the number of new riders on the project, yet again based on ridership prediction. We know that transit expansion by itself doesn’t solve congestion, just as road expansion doesn’t either. But transit expansion can do very important things much better than road expansion: it can allow for drastically more economic growth and development at a fixed congestion level and improve the ability of those who cannot drive to participate in the life of the community.  It does this by expanding the access to opportunity that’s possible without generating a car trip. So, there’s a good role here for access measures as an indirect way to tell us whether a transit project has a high likelihood of providing an option to avoid congestion.

For the Environmental Benefits criterion FTA looks at changes in predicted air pollution, greenhouse gases, energy use, and safety benefits. Most of these factors are calculated based on predicted ridership. So, FTA is building many measures on the questionable assumption that ridership is predictable. Again, we know that greater access tends to mean greater ridership, which means great environmental benefits. Perhaps we need more research to be able to quantitatively tie improvements in job access to environmental benefits. If FTA sticks with its current measures for environmental benefits, it makes the case for using access measures in other criteria even stronger, if nothing else than to provide a wider range of measures that aren’t tied to one modeling outcome.

For its Economic Development criterion, FTA evaluates how likely a project would induce new, transit supportive development in the future by looking at local land use policies. How might access be a useful measure here? It depends a lot on what kinds of real estate investors we have in mind.  The real estate business already calculates car access for practically every site they consider.  They should be encouraged to care about transit access (and they sometimes do).

To Sum Up

All of the FTA’s criteria are attempting to answer the question “Which of these potential transit projects across the US is the best investment and therefore worth of funding?” That begs the question of what we, citizens of the US, think we value about our investments in transit. Access starts with one insight about what everybody wants, even if they don’t use the same words to describe it. People want to be free. They want more choices of all kinds so that they can choose what’s best for themselves. Access measures how we deliver those options so that everybody is more free to do whatever they want, and be whoever they are.

Should we be investing in projects that score well on predictions of what we think people will do in the future? Or should we be investing in projects that we can geometrically prove will drastically increase the average person’s access to opportunity?

Whatever your view on these topics, now is the time to respond to the FTA’s questions!



Miami: A Revised New Network

Esta página está disponible en español aquí.

In 2019 and 2020, we collaborated with Transit Alliance Miami to help them develop a new bus network for all of Miami-Dade County. In April the Final Plan was published and put out for public comment by Miami-Dade Transit and their survey showed that 89% of people wanted to see the changes implemented!  In October 2021, the County Commission approved the plan for implementation.

This is what the existing network looks like:

Frequency coded public transit map excerpt from the existing network centered around Miami, Florida

Existing Network. Colors mean all-day frequency! Purple = 10 minutes or better. Red = 15. Orange = 20. Blue = 30. Green = 60.

And here is the revised network with fewer routes, less duplication, more frequency:

Frequency coded public transit map excerpt from the revised network centered around Miami, Florida

Revised Network. Colors mean all-day frequency! Purple = 10 minutes or better. Red = 15. Orange = 20. Blue = 30. Green = 60.

(This is not our mapping style, by the way.  It’s from a tool developed by Kittelson Associates that lets you move a slider back and forth between the two maps, so that you can see how different they are in the same place.  It can be a little clunky.  Look close for a vertical grey bar and you’ll find you can slide it left and right.  If it isn’t working, reload.)

The revisions to the Better Bus Network since April are relatively modest and include adding back some coverage routes in a few places, some extensions and improvements to service on the beach and a few other corridors. These changes are possible because the revised network provides more service than what we originally planned because the County is now proposing to invest in 7% more bus service than the pre-pandemic network!

As we’ve said before, the Better Bus Network as drawn last year wasn’t what Miami-Dade needed, it was what Miami-Dade could afford. It’s great to see political leaders at the County, led by Mayor Cava, willing to invest in more service to achieve better outcomes.

Miami: Una Nueva de Red de Transporte Público Revisada

This page is available in English here.

En 2019 y 2020, colaboramos con Transit Alliance Miami para ayudarlos a desarrollar una nueva red de transporte público para todo el Condado Miami-Dade. En abril, el Plan Final se publicó para recibir cometarios del público. La encuesta mostró que 89% de la gente quiere que se implementen estos cambios!

Aun así, hubo inquietud sobre algunos cambios y la red de transporte público se actualizó con muchas mejoras basadas en el proceso extenso de participación ciudadana ejecutado por la agencia con el apoyo continuo de Transit Alliance. También han tenido conversaciones con la unión para asegurarse crear un plan fiable que tome en consideración a las personas que operarán el sistema todos los días. Miami-Dade Transit y Transit Alliance han hecho un tremendo trabajo con el proceso de participación ciudadana a lo largo de la pandemia para llevar el proyecto a este punto. Pero, aun así, el trabajo no se ha acabado y deberías prestar atención y participar, especialmente si te gusta este plan revisado.

Así es la red de transporte público actual:

Red de transporte público actual. Los colores indican la frecuencia disponible todo el día! Violeta = 10 minutos o mejor. Rojo = 15. Anaranjado = 20. Azul = 30. Verde = 60.

Esta es la red de transporte público revisada:

Red de transporte público revisada. Los colores indican la frecuencia disponible todo el día! Violeta = 10 minutos o mejor. Rojo = 15. Anaranjado = 20. Azul = 30. Verde = 60.

(este no es nuestro estilo de mapa) Es una herramienta desarrollada por Kittelson Associates que te permite mover la barra gris de un lado a otro para comparar los dos mapas. Así puedes ver como son diferentes en un mismo lugar. Si no funciona, recarga la página.)

Las revisiones que se le han hecho a la red desde abril incluyen reintegrar algunas rutas, extensiones y mejoras al servicio en Miami Beach y otros corredores. Estos cambios son posibles porque la red revisada tiene más servicio de lo que originalmente planificamos. Esto es porque el ahora el Condado está proponiendo a invertir 7% más servicio que antes de la pandemia!

Como hemos dicho anteriormente, la red que dibujamos no es la red que necesita Miami-Dade, sino es la red que pueden pagar con los recursos actuales. Es bueno ver líderes políticos del Condado, liderados por el alcalde Cava, dispuestos a invertir en más servicio para lograr mejores resultados.

Si estás en Miami-Dade, por favor provee comentarios. Miami-Dade Transit tendrá una reunión comunitaria virtual el 8 de septiembre a las 6:30pm Eastern. También tendrán “horas de oficina virtuales” a diferentes horas del 9-10 de septiembre para aquellas personas que tengan preguntas. También puedes tomar la encuesta en la página del proyecto para decirles lo que piensas. Recuerda, si te gusta el plan, ¡lo tienes que decir! Demasiado a menudo, la gente que le gusta el plan no dice nada y los resultados de las encuestas hacen parecer que a nadie le gusta.

Finalmente, la red final se lleva a votación final ante el “Transportation Mobility and Planning Committee” el lunes, 13 de septiembre a las 3:00pm y la “Board of County Commissioners” el martes, 15 de octubre a las 9:30am.

A New Bus Network for Alexandria, Virginia

DASH bus stop with temporary sign displaying service changes

Bus stop with temporary sign displaying service changes

On Sunday September 5, 2021 Alexandria, Virginia will wake up to a new bus system, with a completely redesigned bus network for the City’s transit agency (DASH), major complimentary modifications to the WMATA Metrobus network, and free fares on DASH buses.

The redesigned network in the city is the result of a design process that we guided, in cooperation with the local office of Kimley-Horn, for the City of Alexandria and DASH, and in cooperation with WMATA. The New Network launching on Sunday is constrained by what the City could afford, so it does not increase the total amount of service, but it is just Phase 1 of a ten-year plan to grow bus service in the city to improve service for a growing and densifying city.

Our work with the City, DASH, and WMATA began in 2018, and reached the Draft Plan stage in November 2019. The Draft Plan was designed around the policy direction from the DASH Board that, by 2030, 85% of resources should go toward high ridership service, while the rest should go to coverage service. A major focus of the plan is building up a frequent network by running fewer overlapping and competing lines. That means some trips that a person can make today on one bus might require two buses in the future, but the frequency of service means that total wait time is the same, or less, than today.

Alexandria VA DASH new system map

While overall response to the Draft Plan was very positive, there were some specific concerns about coverage loss on a few streets and the Final Plan was tweaked to add service back to a few areas at the cost of being less generous with service span improvements in the short term. Overall, the New Network still has major benefits with the simplification of the network leading to faster trips for most people going to most places. You can see how the New Network changes trip times with this comparative trip planner we developed for DASH.

When the Alexandria Transit Vision Plan was completed in February 2020, just before the pandemic, there was significant interest in new investment in improved service in the first few years of implementation. The top priority for new funding seemed to be increasing evening and weekend service. At that time, the plan recommended an 8% increase in service in the short-term that could improve evening and weekend service. Specifically, it could increase the percent of residents near frequent service on Saturdays from 36% to 65% and on Sundays from 15% to 59%.

During the planning process in 2018 and 2019, fares were not considered a major issue. When the pandemic hit, DASH and WMATA, like many agencies, went fare free and that raised the prominence of fares as an issue in Alexandria, as it has in many communities. Since then, the Mayor and many City Council members have decided that free fares are a higher priority than evening or weekend service improvements, and have endorsed increasing the transit budget to cover the $1.5 million annual cost of going zero fare this year.

Throughout the planning process we led the network design and guided the stakeholder conversations. We worked closely with our local partners at Kimley Horn who led the public outreach and key local government coordination. And the City and DASH provided strong leadership throughout and have continued to persevere to bring this first phase to life despite all the challenges of managing the Covid pandemic.

So, thanks and congratulations to everyone at WMATA, DASH, and the City who worked hard to get this done.  We hope that everyone who lives in, works in, or visits Alexandria enjoys DASH’s New Network.  We encourage Alexandrians to stay involved in advocating for more and better transit, so that the more frequent 2030 Network can be funded and implemented.

San Francisco: Go Forward by Going Back?

We’re currently working with the San Francisco Municipal Transportation Agency (SFMTA), which manages the city’s transit network called Muni, on options for how to develop their network as the pandemic wanes.  This piece is cross-posted with the SFMTA Blog.

Source: Wikipedia user Pi.1415926535

When a transit agency comes back from the COVID-19 crisis, should it aim to put service back the way it was, or try to put back something better?  That’s the question that the SFMTA will be asking the public later this summer.  

Muni started out as a service that took people downtown, and even today, most of the service is oriented that way. Meanwhile the pandemic accelerated ongoing trends that have shifted travel patterns away from a single focus on downtown and towards many locations across the city.  So are we sure we want the network to be exactly as it was?

Later this summer, the SFMTA will be sharing three alternatives for how service might be restored in winter and inviting the public to provide feedback on those alternatives. The input received from the public will help the SFMTA Board determine the pattern of Muni service to be implemented in early 2022. The three scenarios the SFMTA will be laying out for the public to consider are: 

  1. Return the Familiar Network​
  2. Build a High-Access Network
  3. Develop a Hybrid Network, balancing the best features of the first two.

The Familiar Network alternative would put back the routes people are used to from prior to the pandemic. But the service that people are used to isn’t always the service that helps the most people get where they need to go. 

The High-Access approach would shift some patterns of service to expand people’s ability to get to more destinations sooner. (See here for a full explanation of how access works.)

When we plan for high access, we aren’t just thinking about trips people are making, or the trips they made before the pandemic. We’re also thinking about all the trips they could make. Better access can mean more opportunities in your life. Right now, many people’s lives are changing as they find new jobs, get their kids started at new schools and explore new types of recreation. A high-access network tries to give people as many options as possible. 

What does a high-access alternative mean in practice? Here’s an example from the Richmond District:  Once Line 31 Balboa comes back in August, the Richmond district will have frequent east-west lines spaced every quarter mile. But Muni’s 2 Clement runs just one-eighth mile (a long Richmond block) from the frequent lines on California and Geary.  

Pre-pandemic map of San Francisco’s Richmond district transit services.  Note the consistent spacing of east-west routes every 1/4 mile, but the exception is Line 2-Clement in the upper right.  Source: SFMTA

Closer look at Line 2 Clement, and the more frequent lines 1/8 mile away on either side.

To measure the total access for people in a particular place, we look at all the trips to all the places they might be going, and calculate how long those trips take on the network. This travel time includes walking time, waiting time and riding time. In other words, we measure travel time starting from when you want to go, not when the bus comes.  

When we calculate access from points along Clement, we find that the 2 Clement doesn’t add much, because the nearby service on Geary is so much faster and frequent.  Even if you walk (or roll) slowly at 2 miles per hour, it would take you 8 minutes to get from Clement to Geary.  But your wait would be 5 minutes shorter, on average, because the 38 Geary is so frequent. You may save even more time if you get a 38R Geary Rapid, which is faster. At most, the 2 Clement service only saves riders a minute or two. And if you walk at a more average pace, 3 miles per hour, it’s almost always faster to walk to Geary than wait for the bus on Clement.

Such close spacing of parallel routes is not something the SFMTA provides in most parts of the city, so does it make sense to dedicate Muni’s scarce resources to provide it here? Should those resources go where they can measurably expand access to opportunity, such as by moving toward five-minute frequency on many lines?

I’ve talked at length about this high-access approach because it’s less familiar and therefore requires more explanation, but that doesn’t mean the SFMTA has already decided to do it. The choices between familiar and high-access approaches is a genuine question, and we’ll want to know what you think.

Finally, all of these choices are harder because the SFMTA faces severe resource constraints. It still faces a labor shortage and has lost much of its income from fares and parking revenues, not to mention the structural deficit that existed even before the pandemic.  So the agency can’t afford to restore all of the service it ran before the pandemic.  Even if the labor shortage were resolved (and the SFMTA is working on it), restoring 100% of the previously scheduled service would run the risk that just a year or two later, when one-time federal funding runs out, drastic service cuts would be needed that could leave us with even less service than we have now. 

Instead, it makes sense to offer only a level of Muni service that the SFMTA is sure they can sustain, at least until they find new resources to replace funds that have eroded over the last decade and fallen dramatically during the COVID-19 pandemic.

Next, we and the SFMTA will lay out exact plans for each alternative, showing the exact routes and frequencies that each alternative would provide. We’ll then analyze how each alternative affects access to opportunity.  We’ll look at this for the whole population, but we’ll also calculate the benefits and impacts for specific neighborhoods, for people of color, for low-income people, and for people who walk or roll relatively slowly.  

The SFMTA will bring this information to the community, so that everyone can think about the choices and express their view.  This will help the SFMTA Board reach a decision that reflects the values of San Francisco.  

Where Flying Cars Take Us: A Science Fiction Excursion

As a transport planner with a strong interest in science fiction, I am obviously provoked by this tweet:

Scott is talking about flying cars, a staple of science fiction at least since The Jetsons.  And as it happens, one of the most fascinating science fiction series of recent years — at least for anyone interested in politics, history, philosophy, or public policy — is about a 25th Century world where automated flying Uber has crushed all other modes of transport, creating a dreaded concentration of monopoly power from which flow the crises that drive the plot.

Historian Ada Palmer’s four “Terra Ignota” books, which begin with Too Like the Lightning and will end later this summer with the Perhaps the Stars, tell of a world where globe-spanning flying cars have done away with geographic nations, where “it does not take a firebrand leader to make someone who lives in Maui, works in Myanmar, and lunches in Syracuse to realize the absurdity of owing allegiance to the patch of dirt where babe first parted from placenta.” [p43]  Indeed, at 9,640 km/h, you’ll only need an hour to get from your job in Myanmar to lunch in Syracuse, Italy — and a half-hour longer to get to Syracuse, New York.  (The people of this world seem to have no concept of sonic booms, presumably for the same reason that fish don’t have a concept of water.)

In place of nations 25th Century earth has organized itself into Hives, non-geographic entities that do much of what nations do.  They have governments, laws, shared values, capitals, and cultures, but they don’t control patches of land.  You can choose which one to belong to, and still live anywhere.

For my readers who work in city planning or transport, many skeptical questions now jump to mind, so first let me say this:  These books are superb. They are funny.  They’re erudite but not intimidating, cheerfully explaining the key points of philosophical history when you need to know them.  They are driven by brightly sketched and often endearing characters.  They bristle with sharp ideas about everything from the enduring appeal of monarchy to the minefield of gendered pronouns.  They are especially interested in how societies use and distort the past; this, for example, is a world run by leaders who love an idealized memory of the European 18th Century — the philosophy, the politics, the hoopskirts and wigs — much as the Renaissance (Palmer’s expertise) was built on an idealized memory of ancient Greece and Rome.

This, in short, is what happens when historians write science fiction.  We have lots of science fiction where the science is meticulous but the history and culture are thin.  These books are the opposite.  Here, the technology is lightly and questionably sketched, but the cultural, political, and social consequences of that technology are worked out with stunning detail and plausibility.  Even if I doubt its technological premise, this alternative world — one that hasn’t had a war for centuries — was one that I could believe in while I was inside of it.

Still, all of it is built on universal, cheap, and frictionless flying cars.  There seems to be no reason not to go anywhere in the world, at any time.

After wondering how anything this energy-intensive could be provided in such abundance that people never discuss its cost, the economist asks: Why would there still be cities?  They do exist, and some of them seem to have streets that people walk along, so perhaps people still like being around other people.  Progressive urbanists will breathe a sigh of relief when they encounter these scenes.

But most of the cities we visit are capitals of Hives or of other Hive-like communities, and if we’re not there to see powerful people in secret chambers, then we are often there almost as tourists, seeing the sights and savoring the uniqueness and symbolism of the city.  Maybe the few pedestrian-filled streets that we see are like those of Colonial Williamsburg or Disneyland. We don’t delve into how the cities function beyond their role as stage sets for the drama.  It’s not clear that they function as cities at all.

The city we meet first, Cielo de Pájaros in Chile, is designed to attract vast clouds of birds but lacks commercial districts. It’s a “city designed for for those who don’t like city centers, whose perfect evening is spent by a window, watching gulls and black waves crashing down.” [p31]  Clearly if there’s universal Uber there must also be universal Amazon, delivering fish fresh off the dock from your choice of Portugal or Maine, so maybe nobody needs shops anymore.   But again, if you don’t like the bustle of human activity, why live in a city?  Why not scatter in cabins all along Chile’s coast?

If members of different Hives live side by side while obeying different sets of laws, what law is in force when they interact?  For Palmer this is a simple problem of inter-Hive crime, so she images a system of “polylaw” that brings a neutral justice to bear.  But a city that functions (rather than just symbolizes) needs a much finer shared web of legal and cultural systems.  There must still be rules about where you can land a flying car, or what you can throw in a sewer drain that goes to the local river, or whether you can build a factory next to people’s homes.

In the absence of such rules, we must imagine the libertarian urban world that the unrestrained flying car would make.  In the first chapter, even before you meet a child who performs decidedly religious miracles, you will encounter Palmer’s most unbelievable sentence:

Carlyle bade the car touch down, not on the high drawbridgelike walkaway which led to the main door of the shimmering [house], but by the narrow maintenance stairs beside it. [p14]

You can fly across the world on a car that will land on your preferred side of a house, so that you don’t have to walk even a few steps. Later, we even see this done in Paris.  Even today you shouldn’t expect Uber to come to your exact address in a dense city, and there will be lots of honking if it does. Bus lanes, bike lanes, pedestrians, deliveries — all these things need space in the street.   If a flying car can land in Paris exactly where the customer wants, what does the narrow Parisian street look like? Is there room to walk? What’s left for anything but landing space?

But while city planners may puzzle over these things, Palmer’s books still ask great questions that are at the heart of the question of cities:  Are you sure we should want to “abolish geography”, as so many transport gadget inventors have promised over the years? Would you really want to “live in Maui, work in Myanmar, and lunch in Syracuse,” or would you feel that in a world of such universal travel, all these places have become so identical that you might as well work from home?  If you did that, would you even go for a walk in your neighborhood, meeting familiar people in the flesh, when you could just as easily walk in a city that’s having better weather at the moment?  Will you like a placeless society where you and your neighbor listen to different news sources to the point that you have incompatible views about reality?  If so, would you still be able to cooperate about fixing the fence or agreeing on quiet hours?  And if that incomprehension got out of hand, then whoa, what would a war between Hives be like?

Whatever your first reaction to those questions, Palmer’s books will add nuance to it.  If you enjoy thinking about politics, philosophy, history or public policy (and if you are willing to live without the presumptive atheism of most science fiction) I think you’ll enjoy these books. And I promise: Your skepticism about flying cars will survive the journey.



The Problem with “Improving Transportation”

When you call it that, it’s not very popular.

Looking at this Pew survey, Matt Yglesias points out that Democrats and Republicans seem to agree on the unimportance of improving transportation.


Alas, faced with that, our politicians talk about jobs and infrastructure rather than transportation.  This in turn creates the suspicion that we’re employing people to do nothing or building things we may not need.

But of course, many of the things people seem to care most about (and the two parties agree most about) depend on transportation, notably: “Improving job situation.” “strengthening economy.”  (It’s also important to several things that are sadly more polarizing, such as “dealing with global climate change,” dealing with the problems of poor people,” and “addressing issues around race.”)

I wish we were in the habit of asking people if they care about “access to opportunities“, which captures why we care about jobs but also resonates with other important goals, like economic growth and access to opportunity.

But in any case, transportation  doesn’t poll well.  Maybe that’s fine.  Even I am not that interested in transportation. I’m interested in people being able to do things, as a result fo being able to go places.  Let’s talk about that.