The quantitative data that’s available is far too limited, and likely to lead us to the wrong conclusions.
Reliance on data to solve complex problems is subject to what’s sometimes called the “drunk under the streetlamp” effect: An obviously intoxicated man is on his hands and knees on the sidewalk, under a streetlamp. A passing cop asks him what he’s doing. “Looking for my keys,” the man replies. “Well, where did you drop them?” the cop inquires. “About a block away, but the light’s better here.”
When it comes to transportation planning, we have copious data about some things, and almost nothing about others. Plus, there’s an evident systematic bias in favor of current modes of urban transportation and travel patterns. The car-centric data we have about transportation fundamentally warps the field’s decision-making. Unless we’re careful, over-reliance on big data will only perpetuate that problem—if not make it worse.
To understand why qualitative data can sometimes tell us more, let’s look at some documentation about the way one American transportation system performs.
Three recent essays from people walking in Houston make it clear that, there, the infrastructure and land use patterns that facilitate safe walking often just don’t exist. The following excerpts are snapshots from a large body of qualitative evidence showing that, in many U.S. cities, walking can be a hellish experience.
Writing in Texas Monthly, in an essay entitled “Where the Sidewalks End,” Sukhada Tektel describes her experiences adapting to Houston after living in Mumbai and Toulouse:
David Yearsely wrote a different essay, albeit with a similar title (“Where the Sidewalk Ends”), describing wandering about Houston’s downtown and Third Ward while visiting for an organ music gathering. Even traversing the city’s upscale River Oaks district, he describes long, sidewalk-less stretches outside the walled enclaves of the busy four-lane San Felipe Avenue. In ten miles of walking, he encountered only two other pedestrians, both walking their dogs.
At the Houston Chronicle, David Dorantes wrote, “I want to walk, but Houston won’t let me.” Like many migrants to the Bayou City, he has lived in places where walking is a normal part of everyday life. But not in Houston:
It’s unfair to pick on Houston. Large parts of most American cities, and especially their suburbs, constitute vast swaths of hostile territory to people traveling on foot. Either destinations are too spread out, or there just aren’t sidewalks or crosswalks to support safely walking from point to point. Moreover, walking is so uncommon that drivers have become conditioned to behave as if pedestrians don’t exist, making streets even more foreboding.
From the standpoint of the data-reliant transportation engineer, the problems encountered by Dorantes, Yearsley, and Tektel are invisible—and therefore “nonexistent.” Because we lack the conventional metrics to define and measure, for example, the hardships of walking, we don’t design and enforce solutions or adopt targeted public policies.
When it comes to car traffic, we have parking standards, traffic counts, speed studies, and “level of service” standards. Traffic engineers can immediately tell us when a road is substandard, or its pavement has deteriorated, or its level of service has become (or might someday become) degraded. By stark contrast, there is no comparable vocabulary or metricsfor walking or cycling. We have not collected a parallel array of statistics to tell us that it isn’t similarly as safe, convenient, or desirable to walk or bicycle to common destinations.
Chief Analytics Officer Europe
15% off with code 7WDCAO17
Chief Analytics Officer Spring 2017
15% off with code MP15
Big Data and Analytics for Healthcare Philadelphia
$200 off with code DATA200
10% off with code 7WDATASMX
Data Science Congress 2017
20% off with code 7wdata_DSC2017