Slate has a new series on operations, and
the first article is about queuing. Queuing is an important part of transport planning because nearly all journeys require waiting in line at some point. From the story, here are the main problems people have with waiting in lines:
There are three givens of human nature that queuing psychologists must address: 1) We get bored when we wait in line. 2) We really hate it when we expect a short wait and then get a long one. 3) We really, really hate it when someone shows up after us but gets served before us.
These apply to traffic congestion, waiting for the bus, negotiating construction zones and other aspects of traffic. New York City's newish subway countdown clocks are designed to provide information that makes waiting for the train less onerous. People are happier with their service simply by knowing how long their wait will be even though the total journey time remains the same.
In transport planning we think about how onerous various types of waiting are to the travelers, and sometimes we try to do something about it. For instance, the countdown clocks, freeway ramp meters (
here is one paper by David Levinson et al. on the difficulty of figuring out how onerous delay from ramp meters and congested traffic is), better bus stops, televisions or other diversions at station are all ways to minimize the negative aspects of queuing without actually changing overall travel time much, if at all. (Ramp meters may have larger effects on travel times for some trips.) Given that queuing is such a large part of transport policy, there are still many misconceptions about it.
Consider congestion, which is simply a slow queue. Congestion is viewed in most cases as a cost to society because it represents lost productivity. Eric Dumbaugh examines this relationship in the Atlantic Cities (
story here) and challenges this orthodoxy on the grounds that the most productive cities are also the most congested:
With the help of my research assistant Wenhao Li, I sought to determine whether vehicle delay had a negative effect on urban economies. I combined TTI’s data on traffic delay per capita with estimates of regional GDP per capita, acquired from the U.S. Bureau of Economic Analysis. I used 2010 data for both variables, converted them to their natural logs, and modeled them using regression analysis.
And what did I find? As per capita delay went up, so did GDP per capita. Every 10 percent increase in traffic delay per person was associated with a 3.4 percent increase in per capita GDP. For those interested in statistics, the relationship was significant at the 0.000 level, and the model had an R2 of 0.375. In layman’s terms, this was statistically-meaningful relationship.
This is consistent with Brian Taylor's arguments laid out in
"Rethinking Traffic Congestion," published in Access. Congestion occurs in socially and economically vital places. Of course, congestion occurs in lousy economies, too, which is one of the reasons we always hear of congestion as a cost.
(In the period after World War II queues were viewed as a failure of socialism by people like Winston Churchill and eventually queues were viewed as a sign of economic decline and malaise. (See Joe Moran's work for more on queuing in the UK.
Here is a link to one paper and
here is a book.))
Ultimately, however, not all queues are created equally, and in some cases congestion queues demonstrate economically vibrant areas, and in some cases congestion queues represent scarcity, lack of options and wasted opportunities. The optimal amount of congestion is not zero. If there isn't any congestion or queues in an area the area will seem dead, so we do want some congestion and waiting. A more nuanced understanding of the challenges presented by queues and congestion is needed.
