Chicago truly has a grid

Looking at a map of Chicago or seeing it from above coming in and out of the local airports shows Chicago’s road network is a grid. A recent study examined just how much of a grid it is:

Photo by Benjamin Suter on

It is right to compare Chicago’s street network to something so obsessively exact. A recent academic study, “Urban spatial order: street network orientation, configuration, and entropy,” by Geoff Boeing, looked at the maps of 100 major world cities, and found that Chicago’s “exhibits the closest approximation of a single perfect grid.” Nowhere else have urban planners been so successful in imposing Euclidean order on natural surroundings. On a scale of 0 to 1, in which 1 is a perfect grid, Chicago scores 0.9. (The least-perfect grid is Charlotte, a Sunbelt city whose street system is more entropic than Rome or São Paulo.)

Why such a design?

The man hired to plat a town at the mouth of the Chicago River was James Thompson, a surveyor from Kaskaskia, and the father of the Chicago Grid. Illinois had already been divided into square townships and sections by the Northwest Ordinance of 1785. Since Thompson was subdividing a township section, he simply repeated that pattern in miniature when he designed Chicago’s first street map. It was less than half a square mile, bounded by Kinzie on the north, Washington on the south, Jefferson on the west and Dearborn on the east, but it was the template for a network that would eventually cover the 234 square miles of Chicago—and extend into suburbs beyond its borders…

Thompson’s grid was interrupted only by the river, and by established Native American trails which became diagonal streets: Elston, Clark, Milwaukee, Archer, Ogden. By 1869, the grid had become so integral to the city’s identity that the Tribune boasted, “There is no city where the opportunities for straight streets are so advantageous as in Chicago,” and demanded, “Give us straight, broad streets, running uninterruptedly from one extremity of the city to the other.”…

In our quest for orderliness, Chicago also has the advantage of being one of the flattest cities in the U.S., lying on a plain that was once the bottom of a proto-Great Lake. It would not be practical or possible to impose an uninterrupted grid on Pittsburgh or San Francisco, where streets wind sinuously around hills. As the study notes, “Boston features a grid in some neighborhoods like the Back Bay and South Boston, but they tend to not align with one another. Furthermore, the grids are not ubiquitous and Boston’s other streets wind in various directions, resulting from its age (old by American standards), terrain (relatively hilly), and historical annexation of various independent towns with their own pre-existing street networks.”

This sounds like a perfect storm of factors: a planner who applied methods from the Northwest Ordinance, a unique landscape that was flat and had only one waterway, and a quest for land development and profit with land that could be easily marked and developed.

Of course, this question of spatial order could be combined with consideration of how these different spatial orders are experienced. Do residents of Chicago and visitors have a better experience because of the grid or are cities, like Boston or San Francisco, with different spatial orders more interesting and vibrant? The grid has particular advantages for navigation but has less charm or uniqueness.

The Swiss Cheese Model for dealing with industrial accidents

I was recently reading The Grid by Gretchen Bakke where a discussion of massive power plant brownouts led to discussing two approaches to industrial accidents:

One might be given to think that this blackout might have been prevented if somebody had just noticed as things slowly went awry – if in 2002 all of FirstEnergy’s “known common problems” had been dealt with rather than merely 17 percent of them, if the trees had been clipped, if a bright young eye had seen the static in the screen. But what most students of industrial accidents recognize is that perfect knowledge of complex systems is not actually the best way to make these systems safe and reliable. In part because perfect real-time knowledge is extremely difficult to come by, not only for the grid but for other dangerous yet necessary elements of modern life – like airplanes and nuclear power plants. One can just never be sure that every single bit of necessary information is being accurately tracked (and God knows what havoc those missing bits are wreaking while they presumed to-be-known bits chug along their orderly way). Even if we could eliminate all the “unknown unknowns” (to borrow a phrase from Donald Rumsfeld) from systems engineering – and we can’t – there would still be a serious problem to contend with, and that is how even closely monitored elements interact with each other in real time. And of course humans, who are always also component parts of these systems, rarely function as predictable as even the shoddiest of mechanical elements.

Rather than attempting the impossible feat of perfect control grounded in perfect information, complex industrial undertaking have for decades been veering toward another model for avoiding serious disaster. This would also seem to be the right approach for the grid, as its premise is that imperfect knowledge should not impede safe, steady functioning. The so-called Swiss Cheese Model of Industrial Accidents assumes glitches all over the place, tiny little failures or unpredicted oddities as a normal side effect of complexity. Rather than trying to “know and control” systems designers attempt to build, manage, and regulate complexity in such a way that small things are significantly impeded on their path to becoming catastrophically massive things. Three trees and a bug shouldn’t black out half the country. (p.135-136)

Social systems today are increasingly complex – see a recent post about the increasing complexity of cities – and we have more and more data regarding the components and the whole of systems. However, as this example illustrates, humans don’t always know what to do with all this data or see the necessary patterns.

The Swiss Cheese Model seems to privilege redundancy and resiliency over stopping all problems. At the same time, I assume there are limits to how many holes in the cheese are allowed, particularly when millions of residents might be affected. Who sets that limit and how is that decision made? We’ll accept a certain number of electrical failures each year but no more?