The raison d’etre of the highway engineer is making cars go faster. That’s reflected in chronic complaints about traffic congestion, and codified in often misleading studies, like those produced by the Texas Transportation Institute.
The latest contribution to the literature on inter-metropolitan differences in transportation system performance is titled “Speed.” This new paper from Victor Couture, Gilles Duranton, and Matthew Turner, presents a more systematic set of estimates for comparing travel speeds in different metro areas. The names Duranton and Turner should be familiar to City Observatory readers: they’re the co-authors of “The Fundamental Law of Road Congestion,” which persuasively shows how additional road capacity leads to longer trips and more traffic. One of the complicating factors of speed estimation is that speeds vary by length of trip, time of day, and trip purpose. In general, shorter trips involve lower speed travel. That makes sense: if you’re just traveling a mile or two, especially between your home and some other destination, its likely you’ll travel mostly on local streets, frequently encountering stop signs and traffic signals. But for longer trips, it makes more sense, even if its not the shortest distance, to travel part way on higher speed arterials or limited access freeways. Couture and his co-authors use detailed micro-data on trip taking in the National Household Transportation Survey to estimate variations in speed across metropolitan areas, after controlling for differences in trip distances and other demographic factors.
Some metros have faster roads than others, but speed isn’t everything.
After crunching all the data, they come up with their estimates of which metropolitan areas have the fastest highways, and which have the slowest. Their estimates are expressed as a relative travel time, indexed to the average speed for the 50 large metropolitan areas in their study. Values greater than one represent faster than average speeds (traffic in Louisville travels 22 percent faster than the typical metropolitan area). Values less than one represent slower average speeds (traffic in Miami moves, on average, about 12 percent faster than in the typical metro). Here are the largest metros, ranked from fastest to slowest.
A couple of observations are in order about these data. First, it’s worth nothing the dispersion between the fastest and slowest metropolitan areas. Speeds in the fastest metropolitan area (Grand Rapids) are about 22 percent greater than the median; speeds in the slowest metro area (Miami) are about 12 percent less than the median. Second, the largest, densest and most economically vibrant metropolitan areas have among the lowest speeds. The three largest (New York, Los Angeles and Chicago) are among the six slowest. Seattle and San Francisco, famous for livability and technology clusters are also slower. Third, the fastest speeds tend to be a combination of smaller sunbelt metropolitan areas (Raleigh, Oklahoma City, Nashville), and slower growing smaller cities in the Northeast/Midwest: Grand Rapids, Buffalo, Rochester. Couture and his co-authors were also able to look at differences in travel speeds as they relate to demographic, as well as geographic characteristics. Earlier, we reported their striking finding that African-American drivers travel on average about 8 percent more slowly that white drivers, which strikes us as strong evidence that they’re fastidiously trying to avoid being pulled over for driving while black.
Speeds seem highly correlated with measured traffic congestion. You may recall the recent estimates from Inrix on how congested roads were in major metropolitan areas. We’ve plotted the Couture et al estimates of average speeds against the Inrix estimates of metro area congestion. Keep in mind that the Inrix data are for 2016, while the Couture speed data are from 2008. Despite the 8 year difference in the data estimates, there’s a fairly strong correlation. Traffic moves fastest in the cities that Inrix reports have the least congestion (Louisville, Kansas City) and slower in cities that Inrix says are more congested (Miami, Los Angeles). But as the line on the chart suggests, the relationship between average speed and this particular congestion index is non-linear: the big differences in average speeds is among cities with relatively low levels of congestion; as the congestion index rises (across cities) the speed index falls, but more slowly. This suggests that unless you get a very large reduction in congestion, you don’t see much of an increase in measured speeds.
Just like Keanu Reeves and Sandra Bullock, everyone seems deathly of afraid of going slower. But for cities, and their inhabitants, its far from clear that being the fastest actually gets you anywhere. We’ll take a closer look at the implications of speed tomorrow.
Editors note: In the original version of this post, we got Victor Couture’s surname wrong. We apologize.
Speed: Fast cities
Which cities move the fastest? Does it matter?
The raison d’etre of the highway engineer is making cars go faster. That’s reflected in chronic complaints about traffic congestion, and codified in often misleading studies, like those produced by the Texas Transportation Institute.
The latest contribution to the literature on inter-metropolitan differences in transportation system performance is titled “Speed.” This new paper from Victor Couture, Gilles Duranton, and Matthew Turner, presents a more systematic set of estimates for comparing travel speeds in different metro areas. The names Duranton and Turner should be familiar to City Observatory readers: they’re the co-authors of “The Fundamental Law of Road Congestion,” which persuasively shows how additional road capacity leads to longer trips and more traffic. One of the complicating factors of speed estimation is that speeds vary by length of trip, time of day, and trip purpose. In general, shorter trips involve lower speed travel. That makes sense: if you’re just traveling a mile or two, especially between your home and some other destination, its likely you’ll travel mostly on local streets, frequently encountering stop signs and traffic signals. But for longer trips, it makes more sense, even if its not the shortest distance, to travel part way on higher speed arterials or limited access freeways. Couture and his co-authors use detailed micro-data on trip taking in the National Household Transportation Survey to estimate variations in speed across metropolitan areas, after controlling for differences in trip distances and other demographic factors.
After crunching all the data, they come up with their estimates of which metropolitan areas have the fastest highways, and which have the slowest. Their estimates are expressed as a relative travel time, indexed to the average speed for the 50 large metropolitan areas in their study. Values greater than one represent faster than average speeds (traffic in Louisville travels 22 percent faster than the typical metropolitan area). Values less than one represent slower average speeds (traffic in Miami moves, on average, about 12 percent faster than in the typical metro). Here are the largest metros, ranked from fastest to slowest.
A couple of observations are in order about these data. First, it’s worth nothing the dispersion between the fastest and slowest metropolitan areas. Speeds in the fastest metropolitan area (Grand Rapids) are about 22 percent greater than the median; speeds in the slowest metro area (Miami) are about 12 percent less than the median. Second, the largest, densest and most economically vibrant metropolitan areas have among the lowest speeds. The three largest (New York, Los Angeles and Chicago) are among the six slowest. Seattle and San Francisco, famous for livability and technology clusters are also slower. Third, the fastest speeds tend to be a combination of smaller sunbelt metropolitan areas (Raleigh, Oklahoma City, Nashville), and slower growing smaller cities in the Northeast/Midwest: Grand Rapids, Buffalo, Rochester. Couture and his co-authors were also able to look at differences in travel speeds as they relate to demographic, as well as geographic characteristics. Earlier, we reported their striking finding that African-American drivers travel on average about 8 percent more slowly that white drivers, which strikes us as strong evidence that they’re fastidiously trying to avoid being pulled over for driving while black.
Speeds seem highly correlated with measured traffic congestion. You may recall the recent estimates from Inrix on how congested roads were in major metropolitan areas. We’ve plotted the Couture et al estimates of average speeds against the Inrix estimates of metro area congestion. Keep in mind that the Inrix data are for 2016, while the Couture speed data are from 2008. Despite the 8 year difference in the data estimates, there’s a fairly strong correlation. Traffic moves fastest in the cities that Inrix reports have the least congestion (Louisville, Kansas City) and slower in cities that Inrix says are more congested (Miami, Los Angeles). But as the line on the chart suggests, the relationship between average speed and this particular congestion index is non-linear: the big differences in average speeds is among cities with relatively low levels of congestion; as the congestion index rises (across cities) the speed index falls, but more slowly. This suggests that unless you get a very large reduction in congestion, you don’t see much of an increase in measured speeds.
Just like Keanu Reeves and Sandra Bullock, everyone seems deathly of afraid of going slower. But for cities, and their inhabitants, its far from clear that being the fastest actually gets you anywhere. We’ll take a closer look at the implications of speed tomorrow.
Editors note: In the original version of this post, we got Victor Couture’s surname wrong. We apologize.
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