The Car-Centric Future of Planning Data
Joe Cortright cautions against the dangers in over-estimating the value of data in planning decisions. Though a believer in using data to inform decision making and problem solving, Cortright reminds us that "sometimes the quantitative data that’s available is too limited to enable us to see what’s really going on." Moreover, "incomplete data can lead us to the wrong conclusions."
Cortright chooses the case study of walkability to examine the shortcomings of traditional planning data. After examining reports of the pedestrian experience in Houston (and similar conditions around the country), Cortright states the problem: "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."
Further distorting the focus of planning and engineers is an overabundance of data on car traffic: "we have parking standards, traffic counts, speed studies, and 'level of service standards,'" and "[t]raffic engineers will 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."
The implications of Cortright's argument reach into the future, however, and this is where planners have the power to demand more from policy makers. Recall the recent criticism of the city of Columbus' selection for $50 million in grant money from the U.S. Department of Transportation's Smart City competition—awarded for a project proposal that focuses on autonomous vehicles, rather than public, mass transit. Cortright's concern with the priority on self-driving cars and other futuristic technology:
New technology promises to provide a firehose of data about cars, car travel, car delay, and roadways—but not nearly as much about people. This is a serious omission, and should give us pause about the application of “smart” principles to cities and transportation planning.