Felix Salmon

Traffic congestion datapoints of the day

By Felix Salmon
July 10, 2012

TomTom has released its first congestion indices today, comparing 31 cities in Europe and 26 cities in the US and Canada. (They call that North America, which is a bit disappointing, because I’d dearly love to see how Mexico City compares to other North American cities, and it’s not on the list.) The rankings are interesting, but even more interesting, to me, are the way that the rankings have changed over the past year.

Consider Edmonton, for instance: a town in the midst of a massive oil boom, where road construction can’t even begin to keep up with population growth. That was obvious back in September 2009, in the city’s transportation master plan:

As Edmonton evolves from a mid-size prairie city to a large metropolitan area, it is inevitable that congestion levels will increase, particularly during peak periods. Physical, financial and community constraints in many areas make it unfeasible or even undesirable to build or expand roads to alleviate congestion.

TomTom doesn’t give data as far back as 2009, but at least we can see what direction the city is moving in. Last year, Edmonton had a congestion index of 24%, which means that on average, travel times were 24% longer than they would take if traffic were flowing freely. That meant Edmonton was the 8th most congested city on TomTom’s list. This year, the Edmonton congestion index has plunged to just 13%, placing Edmonton 23rd out of the 26 cities, with an enormous decrease particularly during the evening rush hour:


I have no idea why traffic in Edmonton has improved so much over the past year; certainly I wouldn’t have been at all surprised if it had gotten worse rather than better. But the point here is that there’s an important stochastic element to congestion. Consider New York: in 2008, Mike Bloomberg proposed a congestion charge, which passed muster with city legislators but which was ultimately killed in Albany. Again, we don’t have data for what congestion was like in 2008. But between 2011 and 2012, congestion rates in New York overall fell from 23% to just 17%: a very impressive improvement. And today, New York is only the 15th most congested city on the list — behind metropolitan areas like Tampa, Ottawa, and San Diego.

What’s happened in New York to cause the drop in congestion? You can’t say higher gas prices, since those are a nationwide phenomenon, and don’t explain the drop in relative congestion. Plus, congestion in North America overall has stayed stable at 20% even as gas prices have risen. So if it’s not gas prices, what is it? Could it be all those bike lanes? Could it be that John Cassidy needs to eat some crow, and admit that bike lanes reduce congestion, rather than increasing it?

Perhaps: the jury’s still out. And maybe what we’re seeing here is more a function of random variation, and less a function of anything under the control of New York’s Department of Transportation.

What this report does tell me is that it’s going to be very difficult indeed to judge how effective any congestion-charging system is, just by looking at what happens to congestion after such a charge is introduced. I’m sure that if Edmonton had introduced a congestion charge at the beginning of 2011, the city would have claimed a huge amount of credit for the drop in congestion that resulted. But in fact, as we’ve seen, that drop in congestion would have happened anyway.

I’m planning to talk to the people at TomTom next week, and I’ll ask them whether they have any bright ideas when it comes to separating out causative factors for changes in congestion. In the meantime, we now at least have reasonably reliable league tables for the least pleasant cities to drive in. In North America, you want to avoid Los Angeles and Vancouver; in Europe, you want to avoid pretty much every major city. (Stockholm and London, with congestion charges, both have 27% congestion rates, putting them on a par with the very worst US cities.) But especially avoid driving in Warsaw, Rome, and Brussels. They’re even worse than LA.

Update: JCortright, in the comments, makes the excellent point that these numbers are much better at showing congestion changes within a city than they are at comparing congestion between cities. If you have a 45-minute commute in Atlanta, for instance, as measured on a congestion-free basis, and you’re stuck in traffic for an extra half an hour, then that’s 67% congestion. Whereas if you’re stuck in traffic for 15 minutes on a drive that would take you 15 minutes without traffic, that’s 100% congestion. So this methodology makes denser, smaller cities (like Europe’s) look worse.

5 comments so far | RSS Comments RSS

Re: congestion charges – Bloomberg’s proposal was for Manhattan but TomTom’s data spans most of the TriState area. It would be interesting to see how congestion in NYC’s CBD compares to congestion within the congestion charge zones in cities like London, Stockholm, and Singapore.

Posted by fuller.brandon | Report as abusive

A couple thoughts in the form of questions and hypotheses:

(1) Could the congestion variations in Edmonton and New York be due to annual variations in weather, specifically the number of days with heavy snow or heavy rain? Alternately, perhaps a major road construction project had caused or exacerbated a bottleneck on a major highway, and was completed at some point during this period? (I’m fairly certain that wasn’t the case for NYC, not sure for Edmonton). FWIW, Edmonton has been completing some significant transportation projects over the past couple years – opened a 3.3 mile light rail extension in April 2010, and opened a 13 mile segment of its ring road in November 2011 (http://alberta.ca/NewsFrame.cfm?Release ID=/acn/201111/31460601616BE-98B3-C30F-0 E83C7914578B71B.html).

(2) Does the Europe versus U.S. comparison imply that it will take European levels of congestion to make U.S. commuters use mass transit systems to anything like the same extent that Europeans do? I wonder because my sense, admittedly anecdotal, is that much of the support for expanding rail systems in relatively “new” U.S. cities (e.g., cities like Dallas-Ft. Worth, Denver, Houston, and Atlanta that were designed for car travel) is driven by people thinking, “I personally won’t use that system much, but it sure will be great because other people will and my commute in my car will then be easier.”

Posted by realist50 | Report as abusive


I hope when you meet with the folks at Tom Tom, that you will ask them why their estimates of the congestion index differ substantially from the estimates produced by Inrix.

Inrix, as you may know, uses GPS data from commercial fleets, about 2 million vehicles in all, to monitor travel times on urban highways throughout the US. They compute a travel time index (the ratio of travel times at congested v. uncongested periods). When I compare the Inrix estimates of the travel time index for the same 20 US cities included in the TomTom index, I get a very modest correlation of .48 (R2). In theory, they are measuring exactly the same thing.

If this sort of data is to be useful, we ought to know who is measuring it accurately, or more generally, what seems to be driving the results we observe in different metro areas.

Also, I would hasten to add that the travel time index is a lousy measure of congestion and travel burdens in different metro areas. It only makes sense if you assume (heroically, inaccurately) that trip distances are equal across metro areas.

I’ve spent a good deal of time trying to debunk the use of these travel time indexes as a basis for making inter-metropolitan comparisons of urban transportation system performance: see my paper for CEOs for Cities at
http://www.ceosforcities.org/driven-apar t.

Briefly, if you ignore travel distances, you are implicitly saying that sprawling metros with very long travel distances have less of a congestion problem because a smaller proportion of travel time is due to the difference in congestion, notwithstanding the fact that people in these sprawling metros (Houston, Atlanta, Nashville) are driving dramatically longer distances, on average. There’s an inherent structural bias in the travel time index that makes it appear that denser, more compact metro areas with shorter average travel distances have a “worse’ congestion problem, when in fact, their residents may actually spend less time traveling.

Happy to provide my comparison of Inrix and Tom Tom travel time indices for 20 US metros at your request.


Posted by JCortright | Report as abusive

Interesting that Amsterdam and Copenhagen, which have very heavy bike use, are significantly lower than many other more car centric European cities.

Posted by JustinCormack | Report as abusive

I live in London. I’ve said it before, and I’ll say it again: scooters are the way to go. More practical for longer distances, and with filtering, excellent in cities. I effectively don’t experience any congestion at all in London. You have to live quite a long ways out, and positioned right beside stations on either end of your trip, for any rail-based public transport to be remotely competitive. Trips that take an hour+ owing to bus to and from tube station at one end normally take less than 30 minutes, and the primary thing slowing you down is red lights.

@JustinCormack: I can’t speak for Copenhagen, but central Amsterdam is very small and doesn’t really accommodate cars at all. Probably the traffic flow is structurally different – if you draw straight lines between start and finish, I’d bet fewer would cross in Amsterdam.

Posted by BarryKelly | Report as abusive

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