Category: High-Speed Rail

High-Speed Rail and Connecting Transit

Noah Smith is skeptical about high-speed rail in the United States. He makes a bunch of different arguments against it, but I want to zoom in on the first, the issue of connecting transit, which Noah is far from the first person to bring up. It’s a genuine drawback of rail planning in the United States, but it’s very easy to overrate its importance. Connecting transit is useful, as is the related issue of city centralization, but its effect, serious as it is, is only on already marginal high-speed routes, like Atlanta-Memphis or Dallas-Kansas City. Los Angeles suffers from lacking connecting transit, but it’s also so big that nothing it connects to is marginal. Finally, high-speed rail and urban centralization are not in competition, but rather are complements, as in the history of the TGV.

Connections and centralization

Modal choice is about door-to-door trip times. This is why a large majority of people take a train that takes three hours over a plane that takes one: hardly anyone lives near the airport or has an airport as their ultimate destination. In practice, people are much likelier to be living near and traveling to a destination near a city center station.

The importance of connections then is that connecting urban transit extends the range of the train station. I didn’t live at Gare de Lyon or Gare de l’Est, but I could take the Métro there and it was a short trip, much shorter and more reliable than taking the RER to the airport, which made it easier for me to ride the TGV. With reliable connections, I showed up at Gare de l’Est four minutes before a train to Saarbrücken was due to depart, printed my ticket on-site, and walked leisurely to the platform, boarding still with two minutes to spare.

Regional rail has the same effect, at longer range. It’s not as convenient as urban rail, but it feeds the main intercity rail station and is timetabled, so if the system is punctual, passengers can time themselves to the main train station. In Switzerland the connections are even timed, enabling people who travel from smaller cities like St. Gallen to points west to transfer at Zurich Hauptbahnhof within a short window. However, this is completely absent from France: the regional trains are unreliable, and Paris has through-running on the RER but no single central station that can collect connections from secondary centers like Meaux or Versailles.

Finally, centralization is important because the reach of an urban transportation system is measured in units of time and not distance. Even racists who are afraid of taking the trains in Paris and rely exclusively on cars can take a cab from a train station to their ultimate destination and be there shortly. The average speed of the Métro is low, around 25 km/h, but Paris’s density and centralization mean that it’s enough to connect from the main TGV stations to where one lives or works.

But the US doesn’t have that, right?

What Noah gets wrong is that the US has connecting transit as in Paris in a number of big cities, and nearly every even semi-plausible high-speed line connects to at least one such city. Here’s Noah on New York:

The best thing about using the Shinkansen in Japan is that you can get to and from the high-speed rail station using a dense, convenient network of local trains. In America there is no such network. Thus, when I imagine taking the train from SF to L.A., I imagine taking a scooter or an Uber to and from the train station. In L.A., which is so spread out that I probably won’t stay in a small area, I imagine I’d rent a car. That’s a very different experience from using the Shinkansen in Japan. And in NYC, it would mean dealing with the nightmare that is Penn Station — a thoroughly stressful and inconvenient experience.

Let’s discuss New York now; Los Angeles deserves a separate section in this post. Noah lived on Long Island for years; he could connect to any intercity train by taking the LIRR to Penn Station and changing there. It’s this connection that he describes as a nightmare. But the question is, a nightmare compared to what? It’s clearly far less convenient than the timed Swiss connections, or even untimed connections between the Berlin S-Bahn and intercity trains. But the LIRR is a timetabled train, and while delays happen, they’re measured in minutes, not tens of minutes. Passengers can time themselves to arrive 10 minutes before the intercity train departs, even today.

All of this gets easier if a minimally competent agency is in charge and track numbers are scheduled in advance and printed on the ticket as they are here or in Japan. Penn Station is crowded, but it’s not a stampede crush and people who know their commuter train arrives on track 19 and the intercity train leaves on track 14, as written in the ticket, can make the connection in 3 minutes.

The secondary transit cities of the US are dicier. Their modal splits are all in the teens; San Francisco (excluding Silicon Valley) is the highest, with 17.5%. In that way, they’re comparable to Lyon, Marseille, Nice, Bordeaux, Toulouse, Strasbourg, and Lille. However, the way non-New York transit systems work in the US is, the system is usually semi-decent at ferrying people to and from city center, it’s just not strong for other destinations. In Boston, for example, people could transfer to the subway at South Station or Back Bay and cover a decent chunk of urban destinations. It’s nowhere nearly as good as the options for Paris or Berlin, but it’s not the same as not having any connecting transit.

Destination centralization

The connecting transit critique of high-speed rail in the American discourse goes back at least to the Obama era; Richard Mlynarik used it to argue against what he views as inflated California HSR ridership expectations, and everyone who commented on transit blogs in 2008-9 had to address the critique in one way or another. In 2012, I posted about the issue of destination centralization, that is, that destinations are more centralized than origins, especially at long distance. For example, at the time Manhattan had 22% of New York metro jobs, but 36% of jobs involving out-of-county commuting – and the longer the trip, the likelier one’s destination is to be in Manhattan.

The data I looked at was the distribution of five-star hotels, which are incredibly centralized. Depending on data sources, 50 out of 56 such hotels in metro New York were in Manhattan, or perhaps 36 in 37. In Boston, either all are in Downtown or Back Bay, or all but one are and the one is in Cambridge, a few Red Line stops from South Station. In Philadelphia, they’re in Center City.

In New York, there are clusters of lower-priced hotels outside Manhattan. The biggest such clusters are in strategic locations in Queens, Brooklyn, or North Jersey with maximally convenient access to Manhattan, where tourists and business travelers cluster. Some hotels serve suburban office parks, such as the various Central Jersey hotels I would go to gaming conventions at, but they’re smaller and lower-end.

In the Bay Area, Richard argued in favor of the primacy of San Francisco over San Jose by citing broader data on interregional travel. San Francisco, per his dataset, absolutely dominated. More recent data can be seen here, measuring tourism revenue rather than visitor numbers, but San Francisco with 900,000 people is about comparable to Santa Clara, Alameda, and San Mateo Counties combined with their 4.4 million people. There is also a comparison of international arrivals to San Jose and San Francisco – there are several times as many of the latter; I cannot find domestic arrival numbers for San Jose that might compare with San Francisco’s 26 million visitors in 2019.

The upshot is that high-speed rail does not need to connect two strongly-centered cities to be comparable in ridership to existing lines in Europe and East Asia. It only needs to connect one. People may need to drive to a park-and-ride or take a taxi to the train station, but if their destination is New York or any of the secondary transit cities of the US, it is likely to be fairly close to the train station, even if most employment isn’t.

The Los Angeles exception

Noah is on stronger grounds when he criticizes Los Angeles. Even Los Angeles has 1.5 subway lines connecting to Union Station, soon to be augmented with the Regional Connector, but the city is weakly-centered, and a car or taxi connection to one’s ultimate destination is likely. Moreover, the destinations within Los Angeles are not centered on Downtown; for example, high-end hotels are the most likely to be found on the Westside.

However, there are two saving graces for trains to Los Angeles. The first is that Los Angeles’s transit ridership is so low because the city’s job geography is so decentralized that the network is bad at connecting local origins with local destinations. If it is guaranteed that one of the two points connected is Union Station, the city’s network is still bad for its size, but becomes usable. The under-construction Westside subway will open later this decade, providing decent (if not good) connectivity from the train station to high-end destinations in that part of the region.

The second and more important saving grace is that Los Angeles is huge. The absence of connecting transit is a serious malus for intercity rail, but people can still take a taxi, and that may add half an hour to the trip and a cab fare, but we know what adding half an hour to a three-hour train trip does and it’s a 1.5th-order effect. A 1.5th-order effect can turn a line that is projected to get a marginal 2.5% return on investment into one with a below-cost-of-capital 1.5% return. It cannot do this to lines serving Los Angeles, none of which are economically marginal, thanks to Los Angeles’s size. On my map, the only line connecting to Los Angeles that a straight gravity model doesn’t love at first sight is Los Angeles-Las Vegas, and this is a connection we know overperforms the model because of the unique tourism draw of Las Vegas.

On the same map, the other connection that everyone (including myself until I ran the number) is skeptical of, Atlanta-Florida, has the same issue as Los Angeles-Las Vegas: it connects to a very strong tourism region, and the train station would serve the biggest tourist attractions. (This is also true in the case of Los Angeles, where Anaheim is still supposed to get a station within a short shuttle distance to Disneyland.) So my model thinks it’s only 2.5% ROI, but the strong tourism volume is such that I am confident the model remains correct even with the malus for weak job centralization in both Atlanta and the cities of Florida.

High-Speed Rail and Connecting Transit

Noah makes a broader point portraying intercity and regional public transport in opposition:

Building high-speed rail without having a usable network of local trains instinctively feels like putting the cart before the horse. If I had a choice between being able to train around San Francisco conveniently, or quickly get between SF and San Jose, I’d choose either of those over being able to take a Shinkansen-style train to L.A. or Seattle. The lack of local trains and fast commuter rail simply limits my travel options much more than the lack of high-speed rail. A local train network without HSR is great; HSR lines without local trains seem like something that’s at best slightly better than what we have now.

And yes, I realize that money earmarked for “high-speed rail” sometimes goes to create faster commuter rail, and that’s good. But that doesn’t answer the question of what these maps are for.

Noah is pooh-poohing the connection between intercity and regional transit as “the money sometimes goes to create faster commuter rail,” but he’s underestimating what this means, in two ways.

First, on the Northeast Corridor specifically, any improvement to intercity transit automatically improves commuter rail. The reason is that the most cost-effective speed treatments there are shared. By far the cheapest minutes saved on the corridor come from speeding up the station throats by installing more modern turnouts and removing speed limits that exist due to agency inertia rather than the state of the physical infrastructure. Trains can save two minutes between South Station and Back Bay alone on a high seven to low eight figures budget for rebuilding the interlocking. These improvements speed up commuter rail and intercity rail equally.

Moreover, in higher speed zones, it’s necessary to invest in organization before concrete and schedule trains with timed overtakes. But this too improves the quality of regional rail. Boston-Providence trains need to be electrified and run faster to get out of intercity trains’ way more easily; even with trains holding twice for an overtake, this speeds up Providence-Boston travel by 15 minutes even while adding station stops. New York-New Haven trains had better run faster on both short- and long-distance connections – and the difference between improving intercity rail this way and in a way that is indifferent to integration with regional rail is the difference between doing it for $15 billion and doing it for $150 billion.

And second, in cities that are not traditional transit cities, high-speed rail is a really good catalyst for expanding a central business district around the station. The best example for this is Lyon. Lyon built a dedicated central business district at Part-Dieu, the Metro, and the LGV Sud-Est simultaneously. This was not sequenced as local transit first, then high-speed rail. Rather, the selection of the site for a high-speed rail station, within the city but just outside its traditional center, was simultaneous with the construction of the new business district and of an urban rail system serving it.

This is particularly useful for cities that, by virtue of size (Dallas) or location (Cleveland) could be high-speed rail hubs but do not have strong city centers. In Cleveland, demand for housing in the city is extremely weak, to the point that houses sell for well below construction costs, and demand for city center office space is likewise weak; but a train that gets to Chicago in 2 hours and to New York in about 3:15 can make the area immediately around the station more desirable. In Dallas this is more complicated because it would be the system’s primary city, but a location with convenient rail access to Houston is likely to become more desirable for office space as well. This is not in competition with local transit – it complements it, by giving existing light rail lines and potential commuter rail lines a meatier city center to connect suburban areas with.

Public Transport and Scale

Noah asks what the proposal maps are for. The answer is, they are proposals for improvement in passenger rail. There is a real issue of scale and details, which is why those maps don’t depict literally every connection. For that, there are smaller-scale maps, in the same way there is the TransitMatters proposal for Regional Rail in the Boston area, or maps I’ve made for timed connections in New England and Upstate New York between intercity and regional trains. At lower-altitude zoom there’s also the issue of local connections to buses.

A roadmap like Google Maps or a national planning map, shown at such zoom that the entirety of a continental superstate like the United States is in the field of view, will only include the highest level of the transportation hierarchy. In the case of roads, that’s the Interstates, and the map may well omit spurs and loops. At lower altitude, more roads are visible, until eventually at city scale all streets are depicted.

The same is true of public transit – and high-speed rail is ideally planned as public transit at intercity scale. A continental-scale proposal will depict high-speed rail because it depicts all cities at once and therefore what matters at this level is how to get between regions. A state map or regional map such as for New England will depict all regional connections, and a local map will depict bus connections around each train station. At no point are these in competition for resources – good integrated planning means they all work together, so that improvements in regional rail also enable better bus connections, and improvements in intercity rail enable better regional connections.

Is all of this absolutely necessary? No. France manages to make certain connections work without it, and when I try to model this as a door-to-door trip, it’s a factor of 1.5-2 question, not an order of magnitude question. But a factor of 1.5 question is still serious, and it’s one that resolves itself with good public transit planning, rather than with not building high-speed rail at all.

Modeling High-Speed Rail for Germany

I’ve used a ridership model to construct a proposal for American high-speed rail – but what about the country I live in? There’s an election this year and one of the contested issues is climate change, and with growing passenger rail advocacy, it’s not outside the realm of possibility that there will be a large federal investment in dedicated high-speed lines (“NBS”). So I think it’s useful to model what German intercity rail will look like if there is greater investment in NBSes, culminating in a nationwide network such that ICEs will spend nearly all the time on NBSes or occasionally heavily upgraded legacy lines (“ABS”) rather than on slower lines.

If anything, I’m more optimistic about this network on the 15-year horizon than about American high-speed rail. Germany is slowly building more lines, like Stuttgart-Ulm, with Ulm-Munich, Frankfurt-Mannheim, Hanover-Bielefeld, and Frankfurt-Fulda on the horizon. People are also studying the prospects of a more expansive map as part of Deutschlandtakt additions, but unfortunately many 200 km/h ABSes are considered good enough even if they’re in easy terrain for a 300 km/h NBS, like Berlin-Halle/Leipzig.

The model

The professional way to model ridership is to split the travel zone, in this case the entire country, into very small pieces. I’m instead going to use an approximation with metropolitan areas and divisions thereof. For an illustration of my model’s level of sophistication, see below:

He definitely doesn’t wear a mask on the subway. Credit: Annette Pendlebury.

The gravity model to use is approximately,

\mbox{Ridership} = \mbox{Pop}_{A}^{0.8}\cdot\mbox{Pop}_{B}^{0.8}/\mbox{distance}^{2}

The justification for the exponent 2 in the gravity model is that the elasticity of ridership with respect to trip times appears to be close to -2. The justification for the exponent 0.8 is that it empirically appears true when considering Japanese cities’ Shinkansen ridership to Tokyo; the reason for this is that metropolitan areas comprise many different subsections, and the ones farther from city center have longer effective trip time counting connection time to the train station, and larger metropolitan areas tend to have longer distance from the center to the edge.

In the linked paper, the elasticity remains -2 even at short distances. However, we’re going to assume a minimum distance below which the elasticity vanishes, to avoid predicting infinite ridership as distance goes to zero. If distance is expressed in km, the best-fit constant is 75,000, with populations and annual ridership both in millions, and then if there’s no minimum distance, the model predicts Frankfurt (with 4 million people) to Mannheim (2.8 million, 75 km away) has 92 million annual riders just between the two regions, which is utter nonsense. In Japan, ridership looks like the floor is 500 km. In Germany, I’m going to round this to 2.5 hours, and because in practice it’s a bit more than 500 km, I’m going to round the constant 0.3/2.5^2 down to 1.8. We thus get,

\mbox{Ridership} = 1.8\cdot\mbox{Pop}_{A}^{0.8}\cdot\mbox{Pop}_{B}^{0.8}/\mbox{max}\{2.5, \mbox{time}\}^{2}

The network

This is the current draft of what I think Germany should build:

Blue = existing NBS and ABS lines, red = NBSes to be built

This isn’t too different from past maps I made. Berlin-Hanover is 60 minutes on this map and not 75 as on previous maps; a nonstop Velaro Novo can do it in 60 minutes, and the projected ridership is high enough that a half-hourly stopping train for service to Wolfsburg is viable in addition to a core express service. The branch point in the Rhine-Ruhr is moved to Dortmund, which slightly slows down service to Cologne and requires more tunnels, but improves frequency to the system massively, since Dortmund is a connection point to regional trains. Göttingen-Erfurt is dropped – all it does is connect Hanover and Hamburg with Erfurt, which is very small, and speed up travel to Nuremberg and Munich by 30 minutes, which is interesting but not enough to justify 100 km of high-speed rail.

Frankfurt still has an awkward-looking loop, whose purpose is to permit trains from Mannheim to enter the central tunnel to be constructed from the east and then run through to Cologne. However, this may not be necessary – trains from Cologne to Mannheim could just as well skip Frankfurt Hbf, serving Frankfurt at the airport or at a new station to be constructed at Frankfurt Süd, analogous to Cologne-Deutz for north-south through-trains. The expected traffic level is so high that the hit to Cologne-Frankfurt frequency is not awful, and the network complexity added by the skip isn’t higher than that added by having Frankfurt-Mannheim trains enter the tunnel from both directions depending on onward destination.

The network trip times are expressed in multiples of 15 minutes, with some places where timed connections are desirable, such as Fulda between Berlin-Frankfurt and Hamburg-Munich trains. However, overall, the traffic density predicted by the model is so high that on the stronger lines, like Cologne-Frankfurt, the timetable would not look like an integrated timed transfer system but rather the more continuous rapid transit-style model seen in Japan.

The power of polycentricity

The 0.8 exponent in the formula for ridership means that if we get to divide a single metropolitan area into subregions, then its ridership will increase. This is only justifiable if trains serve all such subregions; if the trains only serve some subregions, then we have to subtract them out. When we analyze New York or Tokyo, we can’t just add up each part of the metropolitan area separately – if we do so we must remove unserved sections like Long Island or Chiba, and the effect turns out to be similar to just lumping the metro area together.

However, in the Rhine-Ruhr, trains do serve nearly all sections of the region. The shape of the network there is such that intercity trains will continue stopping at Dortmund, Bochum, Essen, Duisburg, Wuppertal, Dusseldorf, and Cologne, at a minimum. The only recognizable centers without stops are Bonn and Mönchengladbach, and Bonn is connected to Cologne by streetcar.

Dividing cities and counties that are in the Rhine-Ruhr metropolitan region into the influence zones of the seven cities with stops based on what is the closest, we get Dortmund with 1.8 million, Bochum with 0.5, Essen 2, Duisburg 1, Wuppertal 0.9, Dusseldorf 2.3 (2 if we subtract out Mönchengladbach), and Cologne 2.9. Adding them up with exponents 0.8 is equivalent to considering a monocentric metropolitan core of 18.1 million; if we subtract out Mönchengladbach, it’s 17.6 million. This is enormous – larger than Paris and London, where only one high-speed rail stop is possible per train.

This also means we need to separately consider domestic and international traffic. Randstad is polycentric as well, and at a minimum there should be stops at Utrecht (1 million), Amsterdam (2.5), and Rotterdam (3.5), which means the region acts like a monocentric region of 9 million. The upshot is that if there were a 300 km/h train connecting Utrecht with Dusseldorf and Cologne with onward connections at both ends, and fares were st at domestic ICE rates and not Thalys rates, the connection between the two conurbations alone would generate about 17 million passengers a year. Of course, the model thinks all trip times up to 2.5 hours are equivalent, and the most distant city pair, Rotterdam-Dortmund, would be perhaps 1:45, but onward connections to German cities like Mannheim, Stuttgart, and Hanover are all 2:30 or longer with a 300 km/h Dutch line, and so there are benefits to constructing such a line over running at lower speed within the Netherlands.

To the extent the Frankfurt-Mannheim region can be thought of as a polycentric megaregion, the same is true there. Frankfurt, by which I mean Hesse-Darmstadt minus Bergstrasse, is 3.7 million people; Mainz is 0.6; the Rhine-Neckar (including Bergstrasse) is 2.4 million; Karlsruhe is 1.1 million; Stuttgart is 2.5 million. The model thinks that these regions combined generate 25 million annual trips to the Rhine-Ruhr.

European Urbanism and High-Speed Rail

Europe has a number of strong national high-speed rail networks, providing much inspiration internally as well as abroad, including in the United States. With Americans looking at an infrastructure bill including high-speed rail funding, there’s a lot of discussion about what can port, hence my proposal map. That said, caution is required when doing naive comparisons with Europe. European urbanism doesn’t work the same as American urbanism, in two ways. First, European cities are more compact and transit-oriented than most American cities, which is why I somewhat discount American lines unless at least one city connected has public transit. And second, Europe has more, smaller cities than the rest of the urbanized world. This post concerns the second issue.

French and American urbanism: an example

A few months ago I poked around European and East Asian metro area lists. The upshot is that whereas in the three East Asian democracies 70% of the population lives in metropolitan areas larger than 1 million, in France only 33% does, and the median resident sorted by metro area size lives in a metro region of 350,000.

We can apply the same analysis to the United States. At the CSA level, the median American lives in Sacramento, population 2.6 million, and 68% live in metro areas of at least 1 million; at the MSA level, the median is Milwaukee, population 1.6 million, and 56% live in metro areas of at least 1 million. American metropolitan areas are unusually weakly-centered, especially at the CSA level, but otherwise they’re pretty typical of the urbanized world; it’s Europe that’s unusual in having such small cities.

The upshot is that people who are not used to this peculiarity of Europe who look at a map of European cities focus on million-plus metro areas, which are not the whole story here, especially not in France. This makes Europe look emptier than it is, which can lead people to overrate how much ridership a high-speed rail network would have at a fixed population.

France and the Midwest

Scott Hand posted a map on Twitter superimposing France on the Midwest with Chicago taking the place of Paris, arguing that they are similar in population and area:

This is a good sanity check: your Midwestern network should be of comparable magnitude to the TGV network, rather than much larger. It’s easy to say, Lyon has 2.5 million people, Detroit has 5 million people, so clearly a line to Detroit is twice as good as one to Lyon, right? But no: French urbanism supplies many more small cities, which must be accounted for as well. At the end of the day, the populations are similar, even though, in addition to Chicago, the map has three cities (Detroit, St. Louis, Cleveland) with larger metro areas than Lyon and six more larger than Marseille (Milwaukee, Indianapolis, Nashville, Cincinnati, Columbus, Pittsburgh).

The LGV Sud-Est

It’s tempting to compare Paris-Lyon to Chicago-St. Louis. Yonah Freemark did this in 2009, and Jarrett Walker already pointed out in comments that the LGV Sud-Est was always about much more than this. On hindsight, I’ll add that even that sells the LGV Sud-Est short. High-speed rail between Paris and Lyon unlocked fast service from Paris to not just Lyon but also the following metro areas, all with 2016 populations:

  • Dijon (385,000), demoted from the PLM mainline to a branch but still served
  • Grenoble (688,000)
  • Saint-Etienne (520,000)
  • Chambéry (225,000)
  • Annecy (236,000)
  • Valence (187,000)
  • Vienne (115,000)
  • Bourg-en-Bresse (128,000), not on any direct train but still close enough by regional connection or car

What’s more, TGVs would branch from Part-Dieu along legacy lines to serve these smaller cities, albeit at low frequency. Now, with the LGV extending as far south as Marseille, Valence has a through-station on an LGV just outside the built-up area. There’s also Lyria service to thee major Swiss cities; Geneva, a metro area of 1 million, lies on a low-speed extension of the LGV Sud-Est, 3:11 from Paris.

Other than Geneva, which is invisible on the map because it is farther away, the other cities listed are all very small. In the United States, people don’t usually think of metropolitan areas of such size as urban, because they are extremely dispersed and socially identify as not-urban, and because metropolitan America operates at much larger size classes. But they have recognizable urban cores and their populations must be put into any ridership model trying to train data on TGV ridership. In fact, a gravity model with exponent 0.8 predicts that the combined TGV ridership from Paris to all the above cities, excluding Lyon, is nearly twice the ridership on Paris-Lyon.

And in this context, Chicago-St. Louis simply doesn’t compare. St. Louis is somewhat larger than Lyon, yes, but within 60 km, within which radius Lyon has independent Saint-Etienne, Vienne, Bourg, and Mâcon, St. Louis only has its own exurbs. To find a proper Midwestern comparison for the LGV Sud-Est and its extensions toward Marseille, one must go east of Chicago, toward Detroit and Cleveland. Within 60 km Detroit too only has its own CSA plus Windsor, but that CSA has 5 million people, and the same line also reaches Cleveland (CSA population 3.5 million), Toledo (900,000), and Pittsburgh (2.6 million) and points east.

What this means

Having fewer, larger cities doesn’t make it harder to build high-speed rail. On the contrary – it’s easier to serve such a geography. Asia lives off of such geography; Japan and Taiwan serve nearly their entire populations on just a single line, and Korea does on one mainline with a branch. An Asianized France would be able to serve nearly its entire population on the LGV network as-is without needing low-frequency branches to Chambéry- and Valence-scale cities, and an Asianized Germany would be able to just build an all-high-speed network and connect nearly everyone and not just half the population.

There are small cities that happen to lie on convenient corridors between larger cities, the way Valence is between Lyon and Marseille, or Augsburg and Ulm are between Stuttgart and Munich. Other small cities are close enough to large cities that they’re decently-served by a large city-focused rail network, like Saint-Etienne. Those cities are compact, so a large share of the population has access to the train – this is the explanation for the 0.8 exponent in the gravity model of ridership. But overall, most cities of that scale are strewn haphazardly around the country: examples include Limoges, Amiens, and Caen in France, and Osnabrück, Chemnitz, and Rostock here.

However, this doesn’t mean that, in analyzing the impact of population on ridership, we should just pretend the small cities don’t exist. They do, and they supply extra ridership that isn’t visible if one thinks city = metro area of 1 million or more. It’s an understandable way of thinking, but Europe has a lot of ridership generated from intermediate cities and from cities that have a regional rail connection to a big city or a less frequent direct intercity train, and the models have to account for it.

So yes, that the US has so many large-by-European-standards cities means high-speed rail would work well there. However, it equally means that a naive model that just says “this looks like the LGV Sud-Est” would underperform. A better model has to account for specific city pairs. American city pairs still look okay, even with extreme levels of sprawl at the outer ends, but ultimately this means the US can have a network of approximately the same scope of the LGV network, rather than one that is much denser.

Zoomers Day Trip to Bielefeld on the ICE


There’s a rite of passage every year in Berlin of taking a day trip to Bielefeld, an hour and a half away by ICE, every 10 minutes. The idea is to be able to retort to aging millennials who joke that Bielefeld does not exist than they’ve actually been there.

The Abitur is coming soon, and 12th-grade students are supposed to study, but Adam Mansour, Katja Brühl, Max Kleinert, and Nora Martinek are going in Bielefeld. It is not the best day to travel. Friday is a school day, even if it’s short enough it ended at 13:30, and it’s also a popular travel day so the tickets were a bit more expensive, and Adam had to convince his parents it’s worth spending 80€ and all the Germans do it. But at least today it means they don’t have to wake up at 7:00 tomorrow.

On the train going west, Katja keeps complaining about how the train bypasses Magdeburg because of 1980s-90s politics. She says she was looking for labor-related museums in Bielefeld but couldn’t find any; instead, she talks about how the mayor of Hanover is leading a red-black coalition and it’s not the SPD that she’s voting for in September or the SPD that subsidized childcare in Berlin that let her parents afford to have children.

The other three don’t find her annoying. Max and Nora come from much wealthier families, and Nora’s is scratching 10,000€/month, but when Katja talks about how thanks to education reforms pushed on the Länder by the Green-led federal government she could go to the same school as them, they don’t feel either attacked or guilty. They feel happy that they know her and Adam. They listen to what she says about Jusos and housing, the EU, feminism, or comprehensive schools, and it clicks with them because it’s their world too. They know that there are people who resent that the cities are growing faster and associate immigration with social problems; but they associate immigration with Adam’s parents, or with Nora, who only moved to Germany when she was five but who nobody ever calls an immigrant. Adam, in turn, does get called a Syrian immigrant, even though he was born in Germany, his parents having arrived just before the 2015 wave.

There are some American tourists on the train, talking about how pretty Germany is and how they wished the United States could have such a system. Max leans forward and says, “every time they’re on a train, they talk just about the train,” figuring circumlocutions because the Americans might recognize the German word Amerikaner and realize he is talking about them. Nora and Katja giggle, and Adam then joins too.

Otherwise, they try to distract themselves by talking about the exams and about university plans. All plan to go, and all have been told by teachers that they should get good enough grades to go where they want, but Max wants to study medicine and needs to get a 1.0 to get past the numerus clausus. “Do you want me to test you?” Adam asks him.


They are all competitive about grades, even Katja, who told them once that neoliberal models of academic competition promoted inequality, and the Greens should do more to prevent what she calls the Americanization of German education. But Max told them when they planned the trip last week that he was treating it as his vacation day when he wouldn’t need to think about school.

Getting off the train, they start walking toward city hall; Bielefeld doesn’t have a bikeshare system, unlike Berlin, and bringing a bike on the ICE is not allowed. Adam insists on stopping on the way and taking detours to photograph buildings; most aren’t architecturally notable, but they’re different from how Berlin looks.

They run to the Natural History Museum and the Kunsthalle. The museum closes at 17:00 and they have less than an hour, then less an hour at the Kunsthalle until it closes at 18:00. They furiously photograph exhibits when they don’t have enough time to look at them and talk about them.

Adam is especially frantic at the archeology section, just because of the reminder of what he is giving up. He has read a lot of popular history and for the longest time wanted to go study it, but felt like he wouldn’t be able to get work with a humanistic degree and instead went for the real stream at school. When he met Katja two years ago he felt like this choice was confirmed – Katja for all her political interests is going to study environmental engineering and at no point expressed doubt about it.

Max spits on the Richard Kaselowsky memorial when the staff isn’t looking, distracted by other customers. In Berlin he might not even do this, but in Bielefeld he wouldn’t mind getting thrown out of a museum if worst came to worst. Nora and Adam didn’t know the history so as they go in he tells them Kaselowsky was a Nazi and so was the museum’s founder Rudolf Oetker, and the Oetker heirs had to return a few items that may have been stolen from Jewish owners in the Holocaust.

They find a döner place with good reviews and good falafel for Katja and are eating there. Normally they’d go out and get different things in Berlin, but Bielefeld is still a small city and even with Germany’s rapid immigration in the 2020s it doesn’t have Berlin’s majority-migration-background demographics.

Where they’re sitting overlooks the pedestrianized streets of the old city. There are some bikes, some pedestrians, some walking delivery drones. Berlin has a few of these zones within the Ring but they’re not contiguous and Bild accuses the Greens of promoting car-free zones for everyone except the federal government.

They talk about where they want to go, but Max and Katja are hesitant to publicly say what they feel about where they are. It’s Nora who openly says that she’s having fun and that Bielefeld definitely exists no matter what her parents say, but she wouldn’t want to live here. She doesn’t know if she wants to stay in Berlin – she wants to go to TU Munich, partly to see more places, partly because of some parental pressure to leave home – but Bielefeld feels a little too dörferlich.

They all laugh, and Adam says that judging by how his parents describe Daraa, it was a lot smaller than this. He says that they didn’t ever describe Daraa as especially lively, and always compared it negatively with Berlin when he was young and then eventually they just stopped talking about it, it stopped being important to them. Max and Katja nod and start comparing Bielefeld to parts of Germany they know well through extended family – Max’s father is from Münster and his mother’s family is in Göttingen and Hamburg, Katja’s parents are both from Berlin but her mother has family in Fürstenwalde.

And then somehow it drifts back to the election. Katja is worried the Union might win the election this time, stop free work migration, and freeze the carbon taxes at present levels. Adam doesn’t have family left in Syria but they have a few classmates who have family in India, in Vietnam, in Turkey. For the most part things are okay, but there’s always the occasional teacher or group of students who still think Neukölln and Gesundbrunnen are bad neighborhoods; they know who to avoid because people who are racist always find something negative to say to Adam specifically.

But for now, they have one another, and they have exams to score highly on to move on and go to university, and they have two hours to kill in Bielefeld until the ICE train they booked in advance departs to take them back home.

High-Speed Rail and the Pacific Northwest

The Pacific Northwest seems like the perfect region for high-speed rail: its cities form a neat line from Vancouver to Portland and points south, grow at high rates with transit-oriented development, and have sizable employment cores around the train station. And yet, when I generated my high-speed rail maps, I could only include it as a marginal case, and even that inclusion was charitable:

(Full-size image is available here.)

There’s been a lot of criticism over why I’m including Atlanta-Jacksonville but not Vancouver-Seattle-Portland, and I’d like to explain why the model says this.


The population density in the Western United States is very low. What this means in practice is that cities are far apart – the best example is Denver, a large metropolitan area that is 537 km from the nearest million-plus metro area (Albuquerque). A high-speed line can connect two cities, maybe three, but will not form the multi-city trunk that one sees in Germany or Italy, or even Spain or France. Lines can still make sense if they serve enormous cities like Los Angeles, but otherwise there just isn’t much.

This relates to Metcalfe’s law of network effects. In a dense region, the 500-800 km radius around a city will have so many other cities that network effects are obtained as the system grows. Even Florida, which isn’t dense by European standards, has cities placed closely enough that a medium-size system can connect Miami, Orlando, Tampa, and Jacksonville, and then with a 500 km extension reach Atlanta. The I-85 corridor can likewise accrete cities along the way between Washington and Atlanta and get decent ridership.

In the Pacific Northwest, any intercity infrastructure has to live off Vancouver, Seattle, and Portland – that’s it. Spokane is small, orthogonal to the main line, and separated by mountains; Salem and Eugene are small and Salem is technically in the Portland combined statistical area; California’s cities are very far away and separated by mountains that would take a base tunnel to cross at speed. And Seattle is just not that big – the CSA has 5 million people, about the same as Berlin, which has within 530 km every German metropolitan area.

The model

The model thinks that with Vancouver (2.6)-Seattle (5) at 220 km and Seattle-Portland (3.2) at 280, ridership is as follows, in millions of passengers per year in both directions combined:

City S\City NVancouverSeattle

In operating profits in millions of dollars per year, this is,

City S\City NVancouverSeattle

This is $135 million a year. It’s actually more optimistic than the official WSDOT study, which thinks the line can’t make an operating profit at all, due to an error in converting between miles and kilometers. The WSDOT study also thinks the cost of the system is $24-42 billion, which is very high. Nonetheless, a normal cost for Vancouver-Portland HSR is on the order of $15 billion, a bit higher than the norm because of the need for some tunnels and some constrained urban construction through I-5 in Seattle.

It isn’t even close. The financial ROI is 0.9%, which is below the rate of return for government debt in the very long run. Even with social benefits included, the rate is very low, maybe 2.5% – and once social benefits come into play, the value of capital rises because competing government investment priorities have social benefits too so it’s best to use the private-sector cost of capital, which is 4-5%.

This exercise showcases the value of density to intercity rail networks. You don’t need Dutch density, but Western US density is too low – the network effects are too weak except in and around California. It would be mad to build Atlanta-Jacksonville as a high-speed rail segment on its own, but once the Florida network and the I-85 network preexist, justified by their internal ridership and by the Piedmont’s connections to the Northeast, connecting Atlanta and Jacksonville becomes valuable.


The one saving grace of the Pacific Northwest is growth. That’s why it’s even included on the map. Lines in the 1.5-1.8% ROI region are not depicted at all, namely Houston-New Orleans and Dallas-Oklahoma City-Kansas City-St. Louis, both discounted because none of the cities connected has local public transportation or a strong city center. The Pacific Northwest is not discounted, and also benefits from strong growth at all ends.

The gravity model says that ridership is proportional to the 0.8th power of the population of each city connected. To get from 0.9% to 2% requires a factor of 2.2 growth, which requires each city to grow by a factor of 2.2^0.625 = 1.65.

Is such growth plausible? Yes, in the long run. In 2006-16, Metro Vancouver grew 16%; in 2010-9, the core three-county Seattle metro area (not CSA) grew 16% as well, and the core Portland metro area (again, not CSA) grew 12%. At 16% growth per decade, the populations will rise by the required factor in 34 years, so building for the 20-year horizon and then relying on ridership growth in the 2050s and 60s isn’t bad. But then that has a lot of risk embedded in it – the growth of Seattle is focused on two companies in a similar industry, and that of Vancouver is to a large extent the same industry too.

Moreover, the region’s relative YIMBYism can turn into NIMBYism fast. Metro Vancouver’s housing growth is healthy, but the region is fast running out of developable non-residential areas closer in than Surrey, which means it will need to replace single-family housing on the West Side with apartment buildings, which it hasn’t done so far. Growing construction costs are also threatening the ability of both Vancouver and Seattle to feed commuters into their central business districts by rail – Seattle may have built U-Link for costs that exist in Germany, but the Ballard/West Seattle line is $650 million/km and mostly above-ground, and the Broadway subway in Vancouver, while only C$500 million/km, is still on the expensive side by non-Anglo standards. It’s useful to plan around future growth and safeguard the line, but not to build it just on the promise of future growth, not at this stage.

High-Speed Rail Followup

My high-speed rail map exploded, thanks to retweets on social media from the Neoliberal account and Matt Yglesias, who posted a cleaner map of my proposal made by Twitter follower Queaugie, who even called me a transit guru:

So, first of all, thanks to Queaugie for making this, it’s much cleaner than my drawings on an OpenStreetMap base; I keep advocating for geographically accurate maps, but schematics do sometimes have their uses. But more to the point, I’d like to give some context to why some lines are and are not included.

Some examples of past maps

Mapped proposals for American high-speed rail go back a while. On the Internet, interest exploded in the 2000s, leading to high hopes for California High-Speed Rail and the Obama stimulus. Yonah Freemark made one at the beginning of 2009, which played a role in his rise to become a superstar public transit wonk. The RPA had its own plan rooted in the concept of megaregions: see here for analysis from 2011 and here for a synthetic map. But the map that’s getting the most airplay is by Alfred Twu, which is very expansive to the point of having two transcontinental connections; it was most recently covered in Vox and tweeted by Secretary of Transportation Pete Buttigieg, which generated so much discussion that I chose to crayon US high-speed rail rather than my original intention of picking a city and crayoning urban rail for it.

How my proposal differs

My map differs from past ones in visible ways – for one, it is not connected. At the time I started to make it, I believed there would be four components: Florida, Texas, California, and the general Eastern network. It turned out late in the process that there’s decent demand for Atlanta-Florida travel, enough to justify connecting Florida to the general network. But Texas and California remain disconnected, as does the marginal case of the Pacific Northwest.

Analytically, I project traffic by a gravity model, depending on the product of two metro areas’ populations; Yonah and the RPA have different methodologies. But the emergent difference is, first of all, that I have a less connected network, and second, that there are some glaring omissions. I believe those omissions are justified and would like to explain why – in effect, why other people overrate connections that I do not include.

Amtrak and stagnating regions

New Orleans was the largest city in the South until overtaken by Houston around 1950. This means that the historic rail network of the United States served it amply, as it was large relative to turn-of-the-century America. Amtrak, formed to preserve a skeleton of the preexisting passenger rail network, retained the importance of New Orleans and gave it three distinct long-distance routes: one to Atlanta and New York, one to Chicago, one on the way between Florida and California. This way, there is more Amtrak service to New Orleans today than to Houston, whose metro area is around five times larger.

Proposals tend to build upon what exists. So most people recognize that at transcontinental scale, high-speed rail is uncompetitive, but at the scale of Atlanta-Birmingham-New Orleans it looks like a reasonable line. It should get decent modal split, if built. The problem is that not many people live in New Orleans today. The population one needs to sustain high-speed rail is large, larger than that of your typical early-20th century city. This can be done either via a megacity that drives ridership, as in France or California, or via high population density so that many midsize cities are close together, as in Germany or Florida; the best geography is when both are present, as in Japan, South Korea, China, and the Northeastern US.

The growth of the South in the last 70 years has not been even. Texas has exploded, and so have Atlanta, Nashville, and the cities of the North Carolina Piedmont. In contrast, New Orleans is stagnant. Farther north, on the margins of the South, Missouri has had about the same population growth since 1920 as New York, and has been steadily losing seats in Congress. St. Louis and Kansas City, like New Orleans, were huge hubs for early-20th century America, but their populations are just not good enough for high-speed rail. Chicago-St. Louis can squeak by, but Kansas City is too far. Memphis is in relative decline as well, but manages to piggyback on Nashville, albeit marginally.

Streaming High-Speed Rail Crayoning

People are sharing various maps of the high-speed rail network the US could build if it were interested in alternative transportation, and I promised I’d make one myself. I did this on camera on Twitch a week ago but was not finished, so I streamed it again just now – this is going to be a regular occurrence, always at 18:00 my time every Saturday. There’s a recording, but Twitch is being weird about letting me upload it, so it might make it to YouTube instead.

Here is the map:

A full-size image can be found here. Red lines are high-speed rail. Blue lines are marginal lines: New Haven-Springfield and Milwaukee-Green Bay are good legacy lines that may or may not work as full HSR (the former probably better than the latter), while Nashville-Memphis, the Pacific Northwest system, and Phoenix-Tucson are marginal between no service at all and HSR.

Florida High-Speed Rail

I did the calculations for Atlanta-Florida on camera. I was surprised that it turned out to work out well, even with semi-decent return on investment based on my Metcalfe’s law formulas, around 3%. The rub is that Orlando is pretty big, and even though it is sprawl hell, it is also an unusually strong tourist destination, and the rail line would serve Disney World and Daytona Beach. This makes me more confident in a formula trained on Japanese and European cities with public transit than a connection between two random no-transit medium size cities like Cleveland and Cincinnati.

This itself is an example of Metcalfe’s law in action: the Miami-Orlando-Tampa system by itself only returns 2.2% per the formula, and an extension to Jacksonville 2.6%. I also have more certainty in the figures for the larger system, because the impact of sprawl on mode choice is smaller when distances get longer, because it doesn’t affect the air/rail mode choice as much as the car/rail mode choice.

Even at medium distances, observe that the South Florida urban area is linear, around 20 km wide but more than 100 long, which makes intercity rail service more reasonable. Every county can have a stop, and if the 0.8 exponent in the gravity model formula is applied to counties separately, then the sum rises to 6.1, whereas 7^0.8 = 4.74, which means that this refinement provides a 28% boost to ridership. Orlando is not linear, but its subsidiary metro areas, Lakeside and Daytona Beach, could get stops as well.

Alignment questions

I drew the system in a zoom level 7 on OpenStreetMap, which is too high-altitude to see individual railroads. I tried to approximate existing rail alignments that are worth using, but it’s not perfect, so please do not take the map as any assertion about pixel-level alignment, and even some station decisions can be quibbled with.

However, please do take the map as a definitive assertion about macro-scale alignments. The Northeast Corridor should go via I-95 and not via Hartford. This decision is fairly close and could go either way, though the benefits of HSR in the Northeast are so great that the absolute magnitude of such decisions remains momentous. Elsewhere, the Chicago-Minneapolis line could go along I-94 via Eau Claire or via a more southerly route via Rochester and the Mayo Clinic; I’ve gone back and forth on this, and it’s a second-order question, but I think the Mayo Clinic generates more trips, probably. The Albany-Montreal route could be entirely in the state of New York or take a slight detour through easier terrain in Vermont, which is likely cheaper. Toronto-Ottawa could go via Kingston or Peterborough, but the Peterborough route looks more direct. Chicago-St. Louis is sometimes proposed to detour via Champaign rather than go straight via Bloomington, but the benefit of serving UIUC probably doesn’t justify the extra cost. North Carolina HSR could go via the Triad or direct from Raleigh to Charlotte, but the model says the benefit of serving Greensboro is much greater than that of slightly faster trips coming from bypassing the Triad. Texas is a compromise route extending the under-construction line to Downtown Houston and creating a new leg connecting this system to Austin and San Antonio.

The most contentious questions are in California. HSR there should go via a partially high-speed coastal alignment from San Diego up to Los Angeles, then up the Grapevine and Tejon Pass, then across Altamont Pass and a Dumbarton tunnel. None of these decisions is close, and the official alignment decisions to detour via the Inland Empire and Palmdale and to go via Pacheco are all bad and played a role in the failure of the project. Los Angeles-San Diego is in a way the most frustrating: it was left to a future phase, but a medium-speed rail alignment along the coast could be done relatively quickly with electrification and some strategic investments, speeding up trains to about 1:45.


I talked about frequency a little bit in the video, but not in much detail. The biggest problem is that Philadelphia is set up poorly: ideally trains coming from New York should branch to either Washington or Pittsburgh, but instead, 30th Street Station requires New York-Pittsburgh trains to reverse direction. This can be handled through actual reversal, as is done today at Frankfurt, with 4-minute turnarounds (cf. 10 at Philadelphia), or through having New York-Pittsburgh trains skip Philadelphia, as was historically done, with a stop at North Philadelphia instead.

With that in mind, my best guess, based partly on the model and partly on intra-metropolitan fudge factors like New York-New Haven, is as follows:

  • 8 tph New York-Boston, 4 New York-Springfield
  • 8 tph New York-Washington, 4 New York-Pittsburgh-Cleveland, 4 Washington-Philadelphia-Pittsburgh-Cleveland
  • 8 tph New York-Albany, 4 short Boston-Albany, 8 Albany-Buffalo (4 short), 4 Buffalo-Toronto, 4 Albany-Montreal, 2 short Buffalo-Cleveland
  • 2 tph Cleveland-Detroit, 4 (2 short) Cleveland-Chicago, 2 Chicago-Detroit, 2 Cleveland-Louisville
  • 4 tph Chicago-Milwaukee, 2 Milwaukee-Minneapolis
  • 2 short tph Chicago-St. Louis
  • 4 tph Chicago-Indianapolis, 2 Indianapolis-Cincinnati, 2 Indianapolis-Atlanta
  • 2 short tph Nashville-Memphis
  • 6 tph Washington-Richmond, 2 Richmond-Norfolk, 4 Richmond-Charlotte, 2 Charlotte-Atlanta
  • 2 short tph Miami-Tampa, 2 Miami-Atlanta, 2 Atlanta-Tampa
  • 2 short tph Houston-DFW, 2 short DFW-San Antonio, 2 short Houston-San Antonio
  • 2 short tph Vancouver-Portland (at best)
  • 4 tph Los Angeles-San Diego, 2 Los Angeles-Phoenix, 2 Los Angeles-Las Vegas
  • 2 tph Los Angeles-San Francisco, 2 Los Angeles-San Jose, 2 Los Angeles-Sacramento, 2 San Francisco-Sacramento

No Cafe Cars, Please

European and American intercity train planning takes it as a given that every train must have a car dedicated to cafeteria service. This is not the only way to run trains – the Shinkansen doesn’t have cafe cars. Cafe cars waste capacity that could instead be carrying paying passengers. This is the most important on lines with capacity limitations, like the Northeast Corridor, the West Coast Main Line, the LGV Sud-Est, and the ICE spine from the Rhine-Ruhr up to Frankfurt and Mannheim. Future high-speed train procurement should go the Shinkansen route and fill all cars with seats, to maximize passenger space.

How much space do cafe cars take?

Typically, one car in eight is a cafe. The standard European high-speed train is 200 meters long, and then two can couple to form a 400-meter train, with two cafes since the two 200-meter units are separate and passengers can’t walk between them. In France, the cars are shorter than 25 meters, but a TGV has two locomotives and eight coaches in between, so again one eighth of the train’s potential passenger space does not carry passengers but rather a support service. Occasionally, the formula is changed: the ICE4 in Germany is a single 12-car, 300-meter unit, so 1/12 of the train is a cafe, and in the other direction, the Acela has six coaches one of which is a cafe.

A 16-car Shinkansen carries 1,323 passengers; standard class has 5-abreast seating, but even with 4-abreast seating, it would be 1,098. The same length of a bilevel TGV is 1,016, and a single-level TGV is 754. The reasons include the Shinkansen’s EMU configuration compared with the TGV’s use of locomotives, the lack of a cafe car in Japan, somewhat greater efficiency measured in seat rows per car for a fixed train pitch, and a smaller share of the cars used for first class. An intermediate form is the Velaro, which is an EMU but has a cafe and three first-class cars in eight rather than the Shinkansen’s three in 16; the Eurostar version has 902 seats over 16 cars, and the domestic version 920.

The importance of the first- vs. second-class split is that removing the cafe from a European high-speed train means increasing seated capacity by more than just one seventh. The bistro car is an intermediate car rather than an end car with streamlining and a driver’s cab, and if it had seats they’d be second- and not first-class. A German Velaro with the bistro replaced by a second-class car would have around 1,050 seats in 16 cars, almost even with a 4-abreast Shinkansen even with four end cars rather than two and with twice as many first-class cars.

How valuable are cafes to passengers?

The tradeoff is that passengers prefer having a food option on the train. But this preference is not absolute. It’s hard to find a real-world example. The only comparison I am aware of is on Amtrak between the Regional (which has a cafe) and the Keystone (which doesn’t), and Regional fares are higher on the shared New York-Philadelphia segment but those are priced to conserve scarce capacity for profitable New York-Washington passengers, and at any rate the shared segment is about 1:25, and perhaps this matters more on longer trips.

Thankfully, the Gröna Tåget project in Sweden studied passenger preferences in more detail in order to decide how Sweden’s train of the future should look. It recommends using more modern seats to improve comfort, making the seats thinner as airlines do in order to achieve the same legroom even with reduced pitch, and a number of other changes. The question of cafes in the study is presented as unclear, on PDF-p. 32:

Food and RefreshmentsWillingness to Pay
Coffee machine (relative to no service at all)3-6%
Free coffee and tea in each car6%
Food and drink trolley11%
Restaurant with hot food17%

Put another way, the extra passenger willingness to pay for a cafeteria compared with nothing, 14%, is approximately equal to the increase in capacity on a Velaro coming from getting rid of the bistro and replacing it with a second-class car. The extra over a Shinkansen-style trolley is 3%. Of course, demand curves slope down, so the gain in revenue from increasing passenger capacity by 14% is less than 14%, but fares are usually held down to a maximum regulatory level and where lines are near capacity the increase in revenue is linear.

Station food

Instead of a bistro car, railroads should provide passengers with food options at train stations. In Japan this is the ekiben, but analogs exist at major train stations in Europe and the United States. Penn Station has a lot of decent food options, and even if I have to shell out $10 for a pastrami sandwich, I don’t think it’s more expensive than a Tokyo ekiben, and at any rate Amtrak already shorts me $90 to travel to Boston. The same is true if I travel out of Paris or Berlin.

Even better, if the station is well-designed and placed in a central area of the city, then passengers can get from the street to the platform very quickly. At Gare de l’Est, it takes maybe two minutes, including time taken to print the ticket. This means that there is an even broader array of possible food options by buying on the street, as I would when traveling out of Paris. In that case, prices and quality approach what one gets on an ordinary street corner, without the premium charged to travelers when they are a captive market. The options are then far better than what any bistro car could produce, without taking any capacity away from the train at all.

Electronics Before Concrete, not Instead of Concrete

The Swiss slogan electronics before concrete, and related slogans like run trains as fast as necessary, not as fast as possible, is a reminder not to waste money. However, I worry that it can be read as an argument against spending money in general. For many years now, Cap’n Transit has complained that this slogan is used to oppose bad transit like the Gateway Tunnel and if the money is not spent on public transportation then it may be spent on other things. But in reality, the Swiss slogans, all emphasizing cost minimization, must be reconciled with the fact that Switzerland builds a lot of concrete, including extensive regional rail tunneling in Zurich and intercity rail tunneling. Electronics precedes concrete, but does not always substitute for it; it’s better to think of these planning maxims as a way to do more with a fixed amount of money, and not as a way to do the same amount of project with less money.

The extent of tunneling in Switzerland

Here is a list of tunnels built in Switzerland since the 1980s, when its modern program of integrated timetable-infrastructure-rolling stock investment began:

This is not a small program. Zurich and Geneva are not large cities, and yet they’ve build regional rail trunk tunnels – and Zurich has built two, the most of any German-speaking country, since Berlin and Hamburg only have one of their trunk lines each in tunnel, the rest running above ground. The Mattstetten-Rothrist line likewise does not run at high speed, topping at 200 km/h, because doing so would raise the cost of rolling stock acquisition without benefiting the national integrated timetable – but it was an extensive undertaking for how small Switzerland is. Per capita, Switzerland has built far more intercity rail tunnels by length than France, and may even be ahead of Germany and Italy – and that’s without taking into account the freight base tunnels.

The issue of passenger experience

It’s best to think of organization-before-electronics-before-concrete as a maxim for optimizing user experience more than anything. The system’s passengers would prefer to avoid having to loiter 20 minutes at every connection; this is why one designs timed transfers, and not any attempt to keep the budget down. The Bahn 2000 investments were made in an environment of limited money, but money is always limited – there’s plenty of austerity at the local level in the US too, it just ends up canceling or curtailing useful projects while bad ones keep going on.

In Europe, Switzerland has the highest modal split for rail measured in passenger-km, 19.3%, as of 2018; in 2019, this amounted to 2,338 km per person. The importance of rail is more than this – commuters who use trains tend to travel by train shorter than commuters who use cars drive, since they make routine errand trips on foot at short distance, so the passenger-km modal split is best viewed as an approximation of the importance of intercity rail. Europe’s #2 and #3 are Austria (12.9%) and the Netherlands (11.2%), and both countries have their own integrated intercity rail networks. One does not get to scratch 20% with a design paradigm that is solely about minimizing costs. Switzerland also has low construction costs, but Spain has even lower construction costs and it wishes it had Switzerland’s intensity of rail usage.

Optimizing organization and electronics…

A country or region whose network is a mesh of lines, like Switzerland or the Netherlands, had better adopt the integrated timed transfer concept, to ensure people can get from anywhere to anywhere without undue waiting for a connecting train and without waiting for many hours for a direct train. This includes organizational reforms in the likely case there are overlapping jurisdictions with separate bus, urban rail, and intercity rail networks. Fares should be integrated so as to be mode-neutral and offer free transfers throughout the system, and schedules should be designed to maximize connectivity.

This should include targeted investments in systems and reliability. Some of these should be systemwide, like electrification and level boarding, but sometimes this means building something at a particular delay-prone location, such as a long single-track segment or a railway junction. In all cases, it should be in the context of relentlessly optimizing operations and systems in order to minimize costs, ensure trains spend the maximum amount of time running in revenue service and the minimum amount of time sitting at a yard collecting dust, reduce the required schedule padding, etc.

…leads to concrete

Systemwide optimization invariably shows seams in the system. When Switzerland designed the Bahn 2000 network, there was extensive optimization of everything, but at the end of the day, Zurich-Bern was going to be more than an hour, which would not fit any hourly clockface schedule. Thus the Mattstetten-Rohrist line was born, not out of desire to run trains as fast as possible, but because it was necessary for the trains to run at 200 km/h most of the way between Olten and Bern to fit in an hourly takt.

The same is true of speed and capacity improvements. A faster, more reliable system attracts more passengers, and soon enough, a line designed around a train every 15 minutes fills up and requires a train every 10 minutes, 7.5 minutes, 6 minutes, 5 minutes, 4 minutes. An optimized system that minimizes the need for urban tunneling soon generates so much ridership that the tunnels it aimed to avoid become valuable additions to the network.

The Munich S-Bahn, for example, was built around this kind of optimization, inventing many of the principles of coordinated planning in the process. It had a clockface schedule early, and was (I believe) the first system in the world designed around a regionwide takt. It was built to share tracks with intercity and freight trains on outer branches rather than on purely dedicated tracks as in the older Berlin and Hamburg systems, and some of its outermost portions are on single-track. It uses very short signaling blocks to fit 30 trains per hour through the central tunnel in each direction. And now it is so popular it needs a second tunnel, which it is building at very high cost; area activists invoked the organization before electronics before concrete principle to argue against it and in favor of a cheaper solution avoiding city center, but at the end of the day, Munich already optimized organization and electronics, and now is the time for concrete, and even if costs are higher than they should be by a factor of 2-3, the line is worth it.

Electronics before concrete, not instead of concrete

Switzerland is not going to build a French-style national high-speed rail network anytime soon. It has no reason to – at the distances typical of such a small country, the benefits of running at 300 km/h are not large. But this does not mean its rail network only uses legacy lines – on the contrary, it actively builds bypasses and new tunnels. Right now there are plans for an S-Bahn tunnel in Basel, and for an express tunnel from Zurich to Winterthur that was removed from Bahn 2000. The same is true of other European countries that are at or near the frontier of passenger rail technology. Even the Deutschlandtakt plan, compromised as it is by fiscal austerity, by high construction costs, by a pro-car transport minister, and by NIMBYs, includes a fair amount of new high-speed rail, including for example a mostly fast path from Berlin to Frankfurt.

When you plan your rail network well, you encourage more people to use it. When you optimize the schedules, fare integration, transfer experience, and equipment, you end up producing a system that will, in nearly every case, attract considerable numbers of riders. Concrete is the next step: build those S-Bahn tunnels, those express bypasses, those grade separations, those high-speed lines. Work on organization first, and when that is good enough, build electronics, and once you have both, build concrete to make maximum use of what you have.

High-Speed Rail and Cities

When preparing various maps proposing high-speed rail in Germany, I was told that it looks nice but it overfocuses on the largest cities and not about connecting the entirety of the country. I’ve seen such criticism elsewhere, asserting that high-speed rail is a tradeoff in which the thickest connections get fast trains but the long tail suffers, whereas the medium-speed system of Germany or Switzerland or Austria serves everyone. So with that in mind, let’s look at the actual population served by a Germany-wide high-speed rail program.

I made a proposal last year, but then made some additional tweaks, posted as part of a Europe-wide map. The most important tweak: the main east-west trunk line was extended to Dortmund, which trades off some additional tunneling in the Ruhr for both higher frequency on Berlin-Dortmund and fast, frequent Dortmund-Cologne and Dortmund-Düsseldorf service. To my later map I’ll add one proposal: moving the Hanover-Dortmund tracks so that trains can stop in Bielefeld. Otherwise, take the maps as given.

The question is, what population is served by those maps? The answer of course depends on what this exactly means. The sum total of the populations of the cities served – Berlin, Hamburg, Hanover, Dortmund, Würzburg, Erfurt, Mannheim, etc. – is 18.2 million, or 21% of Germany’s population. But is that the full story? This just includes central cities, where people in many nearby suburbs and satellite cities would travel to the rest of the country via the primary city center anyway.

For example, let’s go down this list of German cities. The largest city without a stop on my proposed network is Bonn. But Bonn is very close to Cologne and there are Stadtbahn subways connecting the two cities, in addition to regional rail lines; Bonn also has a shorter-range Stadtbahn to a suburban station at which some high-speed trains on the Cologne-Frankfurt line call. Is it really correct to say Bonn is unserved? Not really. So its population should be added to the 18.3 million.

Going down the list, the same can be said of Wiesbaden (near Frankfurt), Mönchengladbach (Düsseldorf) and likewise many Rhine-Ruhr cities, Halle (near Leipzig and potentially on some slower Berlin-Erfurt trains like today), Potsdam (near Berlin), Ludwigshafen (near Mannheim), and many others. Some cities remain unserved – the largest is Münster, like a few other northwestern cities not really near anything bigger or on any line – but overall this adds another 5.3 million. So we get 23.6 million, around 30% of Germany’s population.

But that list is just cities of 100,000 people or more, and there are smaller suburbs than that. These form counties (“Kreise”), which should be added as well when feasible, e.g. when they lie on S-Bahn systems of large cities or when they are right across from cities with stations, such as Neu-Ulm to Ulm. For example, the Kreise served by the Munich S-Bahn, excluding the city proper, have a total of 1.3 million people, and people in those suburbs would be connecting to the rest of Germany by train at Munich Hauptbahnhof anyway – a lower-intensity, higher-coverage network would do nothing for them.

Overall, these suburbs add another 18.7 million people. In Berlin I used this list of suburbs; elsewhere, I went by S-Bahn reach, or in a few cases used an entire region where available (Hanover, Göttingen, Fulda). There are a few quibbles on the margin in the gaps between the Frankfurt and Rhine-Neckar and in places that probably should count but aren’t on any big city S-Bahn like Frankfurt an der Oder, but it doesn’t change the big picture: a dedicated high-speed rail network would serve around half of Germany’s population pretty directly.

Very little of the remaining half would be genuinely bypassed the way Magdeburg and Brunswick were when Germany built the Berlin-Hanover line. Regensburg, for example, is and will remain peripheral under any rail plan, with regional connections to Ingolstadt and Nuremberg; high-speed rail serving those cities is the best way to connect it to destinations beyond Bavaria. Kiel, at the other end of the country, is and will always remain connected to Hamburg by regional rail. Münster, genuinely unserved, is not really bypassed, not with how close it is to Dortmund. And so on.

Such a plan cannot serve the entire country, but it can definitely then serve a majority of it. It mostly serves the largest metropolitan areas, but that’s fine – Germany is an urban country, around 40% of the country lives in metro areas of at least 1 million people (defined again mostly by S-Bahn reach, which is a conservative definition by American MSA or French aire urbaine or Japanese MMA standards) and much of the rest is either in metro areas somewhat below the cutoff or in exurbs served by regional trains but not the S-Bahn.