The hamster wheel school of transportation policy
Joe Cortright is a Strong Towns member and writer at City Observatory. Today we're sharing a guest article, reposted from his site with permission.
One of the key metrics guiding transportation policy is speed: How quickly can you get from point A to point B. But is going faster a good guide to how we ought to build better places?
When it comes to driving, in particular, the evidence is that making cars go faster doesn’t make places better to live in. In fact, just the opposite. That becomes clear when we look at a cross-section of cities, and see how the variation in average roadway speeds corresponds to measures of happiness. Cities with higher travel speeds just tend to have more suburban-style development patterns, and require people to drive further for common destinations. Those who live in faster moving places are, on average, less happy with their transportation systems than those who live in slower places. In effect, optimizing a transportation system for speed is just a kind of hamster-wheel school of transportation policy: the wheel goes around farther, but we’re still not going anywhere.
To begin with, we’ve got estimates of the average speed of travel in different metropolitan areas developed by the University of California’s Victor Couture. His data shows that average travel speeds in some metropolitan areas (like Louisville) are 22 percent faster than in the typical large metro area; while in other areas, they are slower. Miami’s speeds average about 12 percent less than the typical metro.
The second part of our analysis considers how happy people are with the transportation system in their metropolitan area. Here, we examine survey data generated by real estate analytics firm Porch. They commissioned a nationally representative survey of residents of the nation’s large metropolitan areas and asked them how they rated their satisfaction with their local transportation system on a scale of 1 to 5, with 5 being very satisfied. We compared these metro level ratings of satisfaction to Couture’s estimates of relative speeds in each metro areas. There’s a bit of a time lag between the two data sources: the survey data is from 2015 while the speed data is from 2008; but the 2008 speed data correlates closely with an independent study of traffic congestion levels in 2016, suggesting that the relative performance of city transportation systems hasn’t changed much in that time period.
Faster Metros don’t have happier travelers.
The following chart shows happiness with the regional transportation system on the vertical axis, and average speed on the horizontal axis. Higher values on the vertical (happiness) scale indicate greater satisfaction; larger values on the horizontal (speed) scale indicate faster than average travel speeds. The data show a weak negative relationship that falls short of conventional significancel tests (p = .16). While there isn’t a strong relationship between speed and happiness, if anything it leans towards being a negative one; those who live in “faster” cities are not happier with their transportation system than those who live in slower ones.
We have a strong hunch as to why traveling faster might not generate more satisfaction with the transportation system. Faster travel is often correlated with lower density, and longer travel distances to common destinations, such as workplaces, schools and stores. If you have a suburban, low density metropolitan area, with great distances between destinations, much of the potential savings in travel time may be eaten up by having to travel longer distances.
A complementary explanation is that places with faster speeds, may be ones where proportionately more travel occurs on higher speed, higher capacity roads, such as freeways, parkways and major arterials, as opposed to city streets. The higher measured speed may a product of traveling long distances at high speeds in some cities, as opposed to cities with much shorter average trips on slower city streets.
Faster travel is correlated with more driving.
To explore this hypothesis, we compared average vehicle miles traveled (VMT) per person per day, as reported by the US Department of Transportation, to the average estimated speeds for metropolitan areas. Both of these sets of observations are for 2008. The following chart shows VMT per capita on the vertical axis and average speed on the horizontal axis. As we thought, there’s a strong positive relationship between speed and distance traveled. People who live in places with faster speeds drive more miles per day.
More driving is associated with less satisfaction with metro transportation.
To tie this all together, we thought we’d look at one more relationship: How does distance traveled affect happiness with an area’s transportation system? This final chart shows the happiness (on the vertical axis) and vehicle miles traveled (on the horizontal axis). Here there is a strong negative relationship: the further residents drive on a daily basis, the less happy they are with their metro area’s transportation system.
We think this chart has an important implication for thinking about cities and transportation. Instead of focusing on speed, which seems to have little if any relationship to how people view the quality of their transportation system, we ought to be looking for ways to influence land use patterns so that people don't have to travel as far.
If we could figure out ways to enable shorter trips and less travel, we’d have happier citizens. It’s time to get off the hamster wheel.
(Top photo source: dbgg1979)
For decades, state and federal highway agencies have justified massive projects with traffic forecast models. But a closer look reveals a troubling pattern of exaggeration, manipulation and outright falsification in these models.