Follow the links above to read the report.
Also, Streetsblog New York City has a good, readable analysis of it here. It opens this way:
Imagine two drivers leaving downtown to head home. Each of them sits in traffic for the first ten miles of the commute but at that point, their paths diverge. The first one has reached home. The second has another twenty miles to drive, though luckily for her, the roads are clear and congestion doesn’t slow her down. Who’s got a better commute?
Shockingly, the standard method for measuring traffic congestion implies that the second driver has it better. The Texas Transportation Institute’s Urban Mobility Report (UMR) only studies how congestion slows down drivers from hypothetical maximum speeds, completely ignoring how long it takes to actually get where you’re going. The result is an incessant call for more highway lanes from newspapers across the country.
“Driven Apart” shows how the key tool contained in the Urban Mobility Report – the Travel Time Index – penalizes cities with shorter travel distances and conceals the additional burden caused by longer trips in sprawling metropolitan areas. It also looks at the reliability and usefulness of the methodology used in the UMR and finds it doesn’t accurately estimate travel speeds, exaggerates travel delays and overestimates the fuel consumption associated with urban travel.
The report essentially makes the point that longer commutes are the main cause of time in traffic, not congestion per se.
“In the best performing cities – those that have achieved the shortest peak hour travel distances – such as Chicago, Portland and Sacramento, the typical traveler spends 40 fewer hours per year in peak hour travel than the average American. In contrast, in the most sprawling metropolitan areas, such as Nashville, Indianapolis and Raleigh, the average resident spends as much as 240 hours per year in peak period travel because travel distances are so much greater. These data suggest that reducing average trip lengths is a key to reducing the burden of peak period travel. Over the past two decades, for example, Portland, Oregon, which has smart land use planning and has invested in alternative transportation, has seen its average trip lengths decline by 20 percent.”
If you want to see the chart showing all the metro areas studied, see page 7 of this link.
On page 10 of that link is a section showing why the report’s authors say the Texas Transportation Institute’s Travel Time Index (the TTI’s TTI?) is flawed. The index is the ratio of average peak hour travel times to average free flow travel times. Here’s what it says, using Charlotte and Chicago as examples:
“Chicago has a TTI of 1.43 (the second highest overall, behind only Los Angeles), while Charlotte has a TTI of 1.25 (just about equal to the average for all large metropolitan areas). This would appear to indicate that urban travel conditions are far worse in Chicago. But the traffic delays in the two regions are almost identical (40 and 41 hours per year, or about 10 minutes per day). Chicago has average travel distances (for peak hour trips) of 13.5 miles, while Charlotte has average travel distances of 19 miles. Because they travel nearly 50 percent farther then their counterparts in Chicago, Charlotte travelers end up spending a lot more time in traffic, about 48 minutes per day, rather than 33 minutes per day.”
But the TTI makes it look as if drivers in Chicago have it worse. But if you look at hours spent in traffic they have it much better. The gives a flawed view of reality, the report says.
In sum, says the report:
“The Urban Mobility Report’s key measure – the Travel Time Index – is a poor guide to policy, and its speed and fuel economy estimates are flawed. In the aggregate, the analysis appears to overstate the costs of traffic congestion three-fold and ignores the larger transportation costs associated with sprawl.”
It points out, for example, “There are strong reasons to doubt the UMR claim that slower speeds associated with congestion wastes billions of gallons of fuel. The UMR estimates of fuel consumption are based on a 29-year-old study of low-speed driving using 1970s era General Motors cars, which is of questionable applicability to today’s vehicles and to highway speeds.”