Category Archives: Urban Systems

Traffic Jams Make Cities Splinter into Subcenters: A rule of urban expansion could guide smarter growth – SciAm

I get quoted by Sarah Fecht in Scientific American (310(2)):

Most of the world’s cities started from an important marketplace or town square. Over time, they developed multiple centers where people could work, shop and play. But why? Some economists have suggested that cities fragment because of agglomeration—businesses that spring up in clusters increase their chances of success.

Yet physicists have arrived at a slightly different explanation: traffic jams. Marc Barthelemy and Rémi Louf, both at the Institute of Theoretical Physics in France, designed a mathematical model to explain how cities and their surrounding suburbs evolve. Their research suggests that as a city grows and congested roadways make it increasingly difficult to get to the center, subcenters emerge along the outskirts. “It’s an interplay between how attractive the place is and how much time it takes to go there,” Barthelemy says. Cities with accommodating transportation networks remain centralized longer, he adds.

The physicists validated their ideas using data from 9,000 U.S. cities and towns of different sizes.

A better understanding of how metropolitan areas evolve could prove useful, considering that two thirds of the world’s population is expected to live in urban areas by 2050, notes David Levinson, a transportation engineer at the University of Minnesota. “There’s a lot of urbanization left to happen,” Levinson says. “If planners imagine a city to take a particular form, but that’s not the way the city wants to behave, we’ll be making unwise investments.”

Barthelemy believes the model could also come in handy for estimating traffic delays, gas consumption and carbon dioxide emissions. “I think that this opens up the path to some really quantitative insights about cities,” he says. “We can take simple mechanisms, simple ingredients, and in the end predict how important properties are scaling with population.”

This article was originally published with the title “The Traffic Effect.”

Peer-to-peer car sharing gains momentum within rental car industry

I was interviewed by Catherine Boardman for the article Peer-to-peer car sharing gains momentum within rental car industry:

“Transportation analyst David Levinson said although traditional car-rental companies will not fade away, there is a niche for peer-to-peer services that can offer a quicker, easier alternative.

‘Apps can erode some of the hassle, and maybe today’s companies are too sclerotic to innovate,’ Levinson said.”

Accessibility and non-work destination choice: A microscopic analysis of GPS travel data


Congratulations to Dr. Arthur Huang for successfully completing and defending his dissertation: Accessibility and non-work destination choice: A microscopic analysis of GPS travel data

The advancements of GPS and GIS technologies provide new opportunities for investigating vehicle trip generation and destination choice at the microscopic level. This research models how land use and road network structure influence non-work, non-home vehicle trip generation and non-work destination choice in the context of trip chains, using the in-vehicle GPS travel data in the Minneapolis-St. Paul Metropolitan Area. This research includes three key parts: modeling non-work vehicle trip generation, modeling non-work, single-destination choice, and modeling non-work, two-destination choice. This research contributes to methodologies in modeling single-destination choice and multiple-destination choice and tests several hypotheses which were not investigated before.

In modeling non-work vehicle trip generation, this research identifies correlation of trips made by the same individual in the trip generation models. To control for this effect, five mixed-effects models are systematically applied: mixed-effects linear model, mixed-effects log-linear model, mixed-effects negative binomial model, and mixed-effects ordered logistic model. The mixed-effects ordered logistic model produces the highest goodness of fit for our data and therefore is recommended.

In modeling non-work, single-destination choice, this research proposes a new method to build choice sets which combines survival analysis and random sampling. A systematic comparison of the goodness of fit of models with various choice set sizes is also performed to determine an appropriate choice set size. In modeling non-work, multiple-destination choice, this research proposes and compare three new approaches to build choice sets for two-destination choice in the context of trip chains. The outcomes of these approaches are empirically compared and we recommend the major/minor-destination approach for modeling two-destination choice. The modeling procedure can be expanded to trip chains with more than two destinations.

Our empirical findings reveal that:

  1. Although accessibility around home is not found to have statistically significant effects on non-work vehicle trips, the diversity of services within 10 to 15 minutes and 15 and 20 minutes from home can help reduce the number of non-work vehicle trips.
  2. Accessibility and diversity of services at destinations influence destination choice but they do not exert the same level of impact. The major destination in a trip chain tends to influence the decision more than the minor destination.
  3. The more dissimilar the two destinations in a trip chain are, the more attractive the trip chain is.
  4. Route-specific network measures such as turn index, speed discontinuity, axis of travel, and trip chains’ travel time saving ratio display statistically significant effects on destination choice.
    Our findings have implications on transportation planning for creating flourishing retail clusters and reducing the amount of vehicle travel.

After working at Valparaiso University last year, he is currently teaching at the University of Minnesota Duluth.

Path dependence

If you don’t know where you’re going, any path will get you there.

Path dependence is the idea that where we are today depends critically on where we were yesterday. Some systems are path independent, those that have a single unique equilibrium. Finding the solutions to some math problems is independent of where you start, as long as you follow a particular algorithm.

However, most systems we deal with on a daily basis have some characteristics of path dependence. Where you live might depend on what job you took, which depends on what your previous job was and where you went to school, and a different decision anywhere along the way would change today’s position.

Nowhere is this more true than transportation. On the one hand, it is obvious that certain locations were destined to be important cities because of significant natural advantages. New York has a deep harbor at the confluence of major navigable river. Chicago is at the pivot point between vast agricultural lands to the Northwest and the shortest land path to the East Coast. It was natural railroads would flow through the point on the map we now call Chicago.

On the other hand, many city sites that were selected for natural advantages in one technological era (The Romans selected London and the Dutch and English chose New York in large part for their capability as ports), remain important even after that technology becomes obsolete. With the logistics revolution and the new dominance of container shipping, London’s shipping has moved northeast to Felixstowe as large container ships cannot easily ply the Thames, while New York’s shipping has migrated to the wide open spaces of New Jersey.

The one-time advantages result in a set of complementary investments and inter-related decisions that take on a life of their own. Because of local trading advantages, commodities markets, banks, insurers, and other related organizations located nearby. A critical mass of those institutions felt no need to migrate just because their initial raison d’être vanished. While a building is under construction, temporary framing will often be used until the more permanent structure is erected. Once the final building can stand on its own, the falsework is dismantled. In a sense, everything is falsework for what comes after.

This kind of mutual complementarity happens repeatedly in transportation. Airplanes are the perfect example of mobile capital. If Amalgamated Airlines no longer wants to serve a particular city pair, the airplane can easily be redeployed elsewhere. Yet 80 years into the commercial aviation industry, airlines today serve mostly the same hubs their predecessors did on the Airmail routes of the 1930s. American Airlines is still in Dallas, United in Chicago, Delta (Northwest) in Minneapolis, and so on.

While very few decisions are completely irreversible, transportation decisions come close. Where we place a right-of-way, or an airport will explain where that facility will be decades, or even centuries from now.

A slight deviation from the efficient path to solve a short term problem today will cost travelers time for years to come. It is important to get the design right for the long term. (Undoubtedly this has social costs, see e.g. I-94 through the Rondo in Saint Paul).

But a slight deviation from the path will also change what the long term is. Build a bridge “here” rather than “there”, and then you will adjust all of the roads feeding into the bridge to meet it “here” (instead of “there”). And then land will be developed along the road to “here” to take advantage of the newly created accessibility, properties will be platted, buildings will be built, travel and trade patterns established, and other critical dependencies will come to assume that the bridge is “here”. At some point, say 50 years in the future, the bridge will need to be replaced. Even if “there” was a better location than “here” initially, after five decades of adaptation, it is quite likely that “here” is better now. The whole may have been better were a different initial decision been made, given conditions at the time. Given current realities, that path must now be foregone.

In transportation we say build it right the first time, because there won’t be a second chance. And that is true. But also remember the world will adapt to whatever we do, and we cannot let the perfect be the enemy of the good.

Evaluating Evanston’s Environs

I went to Northwestern University in Evanston, Illinois to attend the excellent International Transportation Economics Association meeting (we hosted an earlier version in Minneapolis in 2009). My photos are here.

2013-07-12 at 08-06-41

Evanston, like Berkeley, is an historically independent city founded in the 19th century with a major university, connected by rail to the nearby city but that was fully swept into the neighboring larger city (Chicago, Oakland/San Francisco) metropolis with the growth the automobile-highway system. It is what we would today call a first ring suburb, currently housing about 75K people. The town is very pleasant and the weather, as with all my visits to Chicago, was atypically nice. It has a high income (PCI of ~$40K, especially considering that students are counting on future not present income when spending) which adds to its pleasantness, as it ensures it is well maintained, that there is new development, and that storefronts are filled. The homes are generally well-kept, and the University is very much the archetype of university architecture, with both a strong central hand ensuring buildings keep with the look and feel of the campus, and the optimal location along the Lake Michigan waterfront.

The city is more or less on a rectilinear grid plan, though there are several different plans in place which collide awkwardly in downtown. The disadvantage is the impaired navigability of such askew streets. The advantage is the heterogeneity of spaces that are created, allowing more interesting forms and spaces to be created, beyond the uniform grid. It still has the small-town feel, with many low-rise commercial structures and diagonal parking spaces in part of downtown.

2013-07-12 at 08-05-26

Further, (and though I did not go there since my meals were already covered) they have a Pret a Manger, which makes me jealous, as I have to rely on Jimmy Johns for sandwiches (Pret:Johns::Johns:Subway).

Like most college towns in the second decade of the twenty-first century, Evanston has decided to establish green lanes for bikes. Though I did not see many bicyclists using them, school is out of session, and Chicago has just started its bike-sharing program, putting it 3 years behind the Twin Cities.

Strangely, given the relative completeness of the Chicagoland freeway and rail systems, Evanston is not well connected to O’Hare, taxis must use surface streets for extended distances to get to the airport, while rail goes through the city of Chicago.

My favorite part of the airport trip was discovering a Cadillac dealership at Lincolnwood Town Center. Note, doing an Internet search, I find there is also a Lincoln dealership in Cadillac, Michigan. Anyway, “he meant Lexus, but he ain’t know it” (NSFW – language).

2013-07-12 at 08-05-37

Lessons from Exploring Evanston

  • College towns have a head start on economic success.
  • Exploiting naturally provided scenic beauty helps.
  • Airport access is relatively unimportant – most people are not going to the airport most of the time.
  • Locating at the edge of a metropolitan area allows the best of both worlds, access when wanted, isolation when desired.

Grids are for squares: Three reasons to consider alternatives to rectilinear street networks

Just as we have cut the earth into a grid of latitude and longitude (and knowing that each “block” of 1 degree latitude by 1 degree longitude gets smaller and smaller as we approach the poles), we similarly cut our cities and rural areas into a finer mesh from that same grid. Much of this arises from the various large scale ordinance surveys that took places in the Americas, Australia, and India. There are of course grids dating much earlier, to Miletus and Mohenjo Daro among many others. Not all grids are aligned with longitude and latitude, sometimes they align with local landscape features, but most of the modern ones are. (Where grids of different alignments come together, interesting spaces are created). Not all grids are squares, most are more like rectangles.

So why should we have 90-degree rectilinear grids?

The arguments in favor are that it:

  1. simplifies construction and makes it easier to maximize the use of space in buildings,
  2. simplifies real estate by making the life of the surveyor easier,
  3. simplifies intersection management by reducing conflicts compared to a 6-way intersection,
  4. is embedded in existing property rights and so impossible to change.

We in the modern world need not be bound to the primitive tools of the early surveyor, the primitive signal timings of the 1920s traffic engineer, or the primitive construction techniques of early carpenters. And while for existing development we might be locked into existing property rights, for new developments that doesn’t follow.

The arguments against the rectilinear include that it:

  1. is among the least efficient way to connect places from a transportation perspective,
  2. reduces opportunities for interesting architecture,
  3. wastes developable space by overbuilding roads.

There are many designs for non-rectilinear street networks. Ben-Joseph and Gordon (2000) (Hexagonal Planning in Theory and Practice (Journal of Urban Design 5(3) pp.237-265)) summarize a number of the 19th and 20th century designs. Most are simple aesthetic choices, as in Canberra, the planned capital city of Australia, and don’t seem to relate to deeper urban organizational issues.
Rudolf Müller proposed The City of the Future: Hexagonal Building Concept for a New Division. Müller’s plan offsets the 60-degree streets so that they come together in 4-way rather than 6-way intersections (though they are still at 60-degrees and not bent to make 90-degree intersections). This ensures that the cells in the plan are not bisected by roads, and that they are instead hexagonal blocks. This plan loses a lot of areas to ornamental parks in the middle of streets.
The circuity increase associated with a 90-degree rather than 60-degree network is obvious. Circuity (the ratio of Euclidean to Network distance) would be minimized if roads were at 0-degree angles. The downside is that this Euclidean network where everyone traveled in a straight-line would literally “pave the earth“. Leaving aside the downsides for the environment of being so-paved, the more critical trade-off from a transportation perspective is construction costs. More roads are more expensive. So a network design trades-off travel costs accruing over time with the up-front construction and long-term maintenance costs. The optimal network design depends on the land use pattern it aims to serve. (And the land use pattern depends on the network design.) The City of Alonso or Von Thünen, with all jobs downtown merely requires a simple radial network to connect it. A polycentric or fully dispersed (homogeneous) city with everything spread uniformly across space begs for more cross-connections.

Charles Lamb’s City Plan has the streets hexsect the hexagonal cells. In this case, the blocks are really triangles.

There is a large literature on the network design problem. One useful paper: Pierre Melut and Patrick O’Sullivan (1974) A Comparison of Simple Lattice Transport Networks for a Uniform Plain, Geographical Analysis 6(2) pp. 163–173, says:

The objective is to compare construction and transport costs for triangular [60-degree], orthogonal [90-degree], and hexagonal [120-degree] regular lattices as transport networks serving a uniform, unbounded plain. The lattices are standardized so that the average distance from the elementary area to the edge is the same for each. This standardization results in equal construction costs for the three networks; thus, the comparison can be made in terms of route factors [circuity], which favors the triangular lattice over the other two.

Because the circuitous network is less efficient, more network pavement and track and vehicle mileage must be provided to enable the same amount of transportation.

This wastes spaces that could be better allocated to non-transportation purposes.
The lattice itself comprises a single level in a hierarchical system. Selected links in a lattice can be reinforced to make them faster, attracting traffic. This process of reinforcement is natural with investment rules that favor more heavily trafficked routes and explains the hierarchy of roads. If it is based on simple reinforcement of existing links rather than creation of new links, that hierarchy will not affect the topology of the network.

Ask MetaFilter has an interesting thread on Comparing perimeters of arrays of hexagons vs. squares – geometry tiling resolved . A key point is that arranging hexagons into a square-like shape has a higher perimeter than arranging squares into a square-like shape.

__    __    __    __    __
/  \__/  \__/  \__/  \__/  \
\__/  \__/  \__/  \__/  \__/
/  \__/  \__/  \__/  \__/  \
\__/  \__/  \__/  \__/  \__/
/  \__/  \__/  \__/  \__/  \
\__/  \__/  \__/  \__/  \__/
/  \__/  \__/  \__/  \__/  \
\__/  \__/  \__/  \__/  \__/
/  \__/  \__/  \__/  \__/  \
\__/  \__/  \__/  \__/  \__/
Diagram 1. Sample hex map

Jellicle wrote:

I think your problem is this – to minimize the perimeter of n hexagons, when you add each new hexagon to the previously-existing group, you have to add it in such a way that touches the most neighbors possible. You would never add a hexagon that touches only on one face if you could add it somewhere else where it touches two faces or three faces, right? If you look at diagram 1 here (which is hexes in a grid shape), you see several hexes at the four corners which touch only on two faces, while there are areas on the outer surface at the top and bottom where those hexes could be placed where they would touch on three faces instead of two. So simply moving those four corner hexes would reduce the perimeter without changing the surface area.

Yet we know the hexagon is efficient, it replicates the closest packing of circles. (Take a penny, surround it with pennies so that they are all tangent. The central penny touches six others.) Thus following the closest-packing argument, the hexagon as geometrical shape is not sufficient for efficiency, we must also arrange those shapes into an efficient pattern, in this case, something more like the Glinski Chess Board:
Much of the inspiration for thinking about hex-maps comes from the gaming community, where such maps have been used since the 1961, when a Hex map was used for the Avalon Hill game Gettysburg. It has since become a standard that is widely used to represent directions of movement in games.

So, although we talk about “grids” as being necessary for connectivity, we can get even more connectivity if we think about a variety of different geometries. It would be a shame if we got locked into grid geometries for new developments when there are so many alternatives to be had.

See also: Home is Where the Hub Is.

Travel Time Perception Errors: Causes and Consequences

Congratulations to soon to be Dr. Carlos Carrion (shown in the center of the picture, between alums Nebiyou Tilahun and Pavithra Parthasarthi), who recently defended his Ph.D. Thesis “Travel Time Perception Errors: Causes and Consequences” (a draft of which is linked). He is working as a post-doctoral researcher at MIT/SMART in Singapore.

Travel Time Perception Errors: Causes and Consequences
This research investigates the causes, and consequences behind travel time perception. Travel times are experienced. Thus, travelers estimate the travel time through their own perception. This is the underlying reason behind the mismatch between travel times as reported by a traveler (subjective travel time distribution) and travel times as measured from a device (e.g. loop detector or GPS navigation device; objective travel time distribution) in collected data. It is reasonable that the relationship between subjective travel times and objective travel times may be expressed mathematically as: Ts = To + ξ. Ts is a random variable associated with the probability density given by the subjective travel time distribution. To is a random variable associated with the probability density given by the objective travel time distribution. The variable ξ is the random perception error also associated with its own probability density. Thus, it is clear that travelers may overestimate or underestimate the measured travel times, and this is likely to influence their decisions unless E(ξ) = 0, and Var(ξ) ≈ 0. In other words, travelers are “optimizing” (i.e. executing decisions) according to their own divergent views of the objective travel time distribution.
This dissertation contributes novel results to the following areas of transportation research: travel time perception; valuation of travel time; and route choice modeling. This study presents a systematic identification of factors that lead to perception errors of travel time. In addition, the factors are related to similar factors on time perception research in psychology. These factors are included in econometric models to study their influence on travel time perception, and also identify which of these factors lead to overestimation or underestimation of travel times. These econometric models are estimated on data collected from commuters recruited from a previous research study in the Minneapolis-St. Paul region (Carrion and Levinson, 2012a, Zhu, 2010). The data (surveys, and Global Positioning System [GPS] points) consists of work trips (from home to work, and from work to home) of subjects. For these work trips, the subjects’ self-reported travel times, and the subjects’ travel times measured by GPS devices were collected. Furthermore, this dissertation provides the first empirical results that highlight the influence of perception errors in the valuation of travel time, and in the dynamic behavior of travelers’ route choices. Last but not least important, this dissertation presents the most comprehensive literature review of the value of travel time reliability written to date.

$40bn “fix it first” plan headlines Obama’s infrastructure push

I get quoted in Global Construction Review: $40bn “fix it first” plan headlines Obama’s infrastructure push

In his State of the Union address last month, US President Barack Obama proposed investing $50bn, starting right away, on the country’s transportation infrastructure.
Of that, $40bn would go toward the upgrades most urgently needed on highways, bridges, transit systems, and airports in what the White House has dubbed a “fix-it-first” policy.
“The national transportation system faces an immense backlog of state-of-good-repair projects, a reality underscored by the fact that there are nearly 70,000 structurally deficient bridges in the country today,” the White House said in a statement.
Mr Obama’s plan, which would need congressional approval, also proposes attracting private investment by pairing federal, state, and local governments with private capital, in what’s being called the “Rebuild America Partnership”.
And a third plank in the President’s infrastructure push is cutting red tape. Through a “historic modernisation of agency permitting and review regulations, procedures, and policies”, the President hopes to cut in half the duration of typical infrastructure projects.
The “fix-it-first” element of the plan received a muted welcome from Professor David M Levinson, an expert on the economics of infrastructure at the University of Minnesota.
“The priority should clearly be on repair because most of the system is built out, and we’ve had nationally declining travel over the last 10 years, so there’s not a major need for expansion nationally,” he told GCR.
The American Society of Civil Engineers (ASCE) has warned of an investment gap of $846bn in surface transportation
“The general problem is that the median age of an interstate highway link in the US is almost 50 years old now, and the expected lifespan of such links was in the order of 50 years.
“Generally most of the infrastructure that has got to be there 10 years from now is there now, and if we want it to be there ten years from now we need to fix it.”
The American Society of Civil Engineers (ASCE) has warned of an infrastructure investment gap, between now and 2020, of $846bn in surface transportation. If not addressed, says the ASCE, this shortfall will hurt the US economy.
Is $40bn enough?
“No,” Prof Levinson said. “No one really knows what’s enough. It’s about the equivalent of one year’s federal spending on roads. So it would be like adding an extra year to the decade, or 10% more over 10 years. It’s not trivial. It’s not going to solve the problem, either, but it’s a real amount of money.”
He also questioned the wisdom of infrastructure investment driven by the federal government.
“The states should be addressing this,” he said. “They can prioritise things locally, they know where the issues are, and they’re the beneficiaries.
“They know how much they need to spend locally to satisfy the local risk-reward, benefit-cost ratio. The federal government allocates things by formula and that means there’s a major inefficiency there.”