CityLab have put together an excellent summary on the concept of induced travel demand, that we have discussed many times over the years. It’s a really good piece because it pulls together a lot of different points on induced demand into one place.
It starts off with a great example of induced demand, from Texas:
With 26 lanes at its widest point, the Katy Freeway in the Houston metro is the Mississippi River of car infrastructure. Its current girth, which by some measures makes it the widest freeway in North America, was the result of an expansion project that took place between 2008 and 2011 at a cost of $2.8 billion. The primary reason for this mega-project was to alleviate severe traffic congestion.
And yet, after the freeway was widened, congestion got worse. An analysis by Joe Cortright of City Observatory used data from Houston’s official traffic monitoring agency to find that travel times increased by 30 percent during the morning commute and 55 percent during the evening commute between 2011 and 2014. A local TV station found similar increases.
The Sisyphean saga of the Katy Freeway is a textbook example of a counterintuitive urban transportation phenomenon that has vexed drivers, planners, and politicians since the dawn of the automobile age: induced demand.
So what is induced demand? At it’s core, it’s a very simple concept – that people respond to incentives. If you make it easier to drive at peak times, more people drive at peak times. The CityLab piece explains how there’s both short-term and long-term versions of induced demand:
Induced demand is often used as a catch-all term for a variety of interconnected effects that cause new roads to quickly fill up to capacity. In rapidly growing areas where roads were not designed for the current population, there may be a great deal of latent demand for new road capacity, which causes a flood of new drivers to immediately take to the freeway once the new lanes are open, quickly clogging them up again.
But these individuals were presumably already living nearby; how did they get around before the expansion? They may have taken alternative modes of transport, traveled at off hours, or not made those trips at all. That’s why latent demand can be difficult to disentangle from generated demand—the new traffic that is a direct result of the new capacity. (Some researchers try to isolate generated demand as the sole effect of induced demand).
Initially, faster travel times (or the perception of faster travel times) encourage behavioral changes among drivers. An individual may choose to take the new highway to a more distant grocery store that has cheaper prices. Trips that may have been accomplished by bike or public transportation might now be more attractive by car. More distant leisure and business opportunities might suddenly seem worth the trip. In aggregate, these choices put more cars than ever before on the newly expanded road, increasing net vehicle miles traveled (VMT) (and greenhouse gas emissions).
In the longer term, roadway expansions make an impact on the human and economic geography of an urbanized area. Businesses that rely on trucking are more likely to locate near these new roads. With those new jobs, and access to countless more via the higher capacity road, housing developments and shopping centers spring up nearby. Urban form responds to existing infrastructure: Roadway capacity expansions spawn autocentric development patterns that utilize the new roads.
These short- and long-term effects eventually bring the expanded road back to its self-limiting equilibrium—in other words, back to capacity, fulfilling Downs’ Law of Peak Hour Traffic Congestion.
In this paper from the Victoria Transport Policy Institute, author Todd Litman looks at multiple studies showing a range of induced demand effects. Over the long term (three years or more), induced traffic fills all or nearly all of the new capacity. Litman also modeled the costs and benefits for a $25 million line-widening project on a hypothetical 10-kilometer stretch of highway over time. The initial benefits from congestion relief fade within a decade.
One question that comes up a bit about induced demand is whether it also applies to public transport. The answer, of course, is yes. Auckland is a great example of how improving our PT system over the past decade has resulted in many many more people using it. However, for public transport, induced demand is almost always a good thing. It supports more frequent services, which means less waiting for customers and ultimately it can justify major infrastructure improvements that deliver much faster and more reliable travel times. In contrast, travelling by car only gets worse as travel demand increases.
Despite induced demand being well accepted in the transport profession, the extent to which it is taken into account in business cases and other transport assessment processes remains very unclear. I know that some transport models simulate some forms of induced demand (routes and modes) but not others (land-use changes and travel at different times of day). Furthermore, it still seems as though the travel time savings benefits are assumed to be maintained over time, whereas Todd Litman’s graph highlights they are usually gone after 10 years.