Transportation systems are vital to cities and their residents. Roads, rails, and trails connect communities to one another, to local amenities, and to economic opportunities.
But transportation networks can also divide, cutting people and communities off and concentrating adverse effects in some areas while sparing others. Even a quick glance at mid-20th-century urban planning in the U.S. shows how transportation decisions ripped apart Black and brown communities in order to build interstates that better connected white suburbs to downtown cores. That same story can be told in Miami, Houston, Detroit, and countless other places around the country during the construction of the interstate system.
Many stakeholders have long been working to rectify this harm, in part by advocating for government agencies to apply an equity lens to their planning and policymaking. Now the U.S. Department of Transportation is taking steps toward change, issuing a request for information this year on data and methods to advance racial equity in transportation systems.
There is an enormous amount of work that must happen to make American cities, towns, and transportation networks more equitable, and high-quality, timely, and privacy-sensitive data has a central role to play in ensuring better outcomes.
At Replica, we recognize that there is no one-size-fits-all approach to transportation and infrastructure planning, and each place has different needs along its path to creating a more equitable future. Still, there are common themes across American cities and towns that can be revealed and addressed with the right data. In our comments to USDOT, we demonstrated several ways that data can inform the decisions that must be made to make more resilient, equitable, and livable places.
Disaggregated data is one of the most powerful tools public agencies can use to assess inequities in the built environment. It’s not enough to know the demographics of neighborhoods, census tracts, or transit riders as a group — a fact the Biden administration notes in its Executive Order on Advancing Racial Equity:
Many Federal datasets are not disaggregated by race, ethnicity, gender, disability, income, veteran status, or other key demographic variables. This lack of data has cascading effects and impedes efforts to measure and advance equity.
Equally important in the context of urban planning is ensuring that data doesn’t infringe on anyone’s privacy. That’s why Replica builds its models by simulating real-world activity with populations that match the Census-reported demographics of each place at each geographic level. This simulated approach gives public agencies access to powerful disaggregated racial and economic data so they can study transportation equity without compromising the privacy of the very people they are working to help.
Some inequities in transportation are clear, like major highways cutting through poor neighborhoods while bike and pedestrian investments concentrate in wealthier ones. Other inequities are less obvious but just as real. Here are a few examples of how high-quality data can assist agencies in their efforts to improve transportation equity.
See who is underserved by public transit. Equitable transit service is about many things, including where routes exist, when they operate, how reliable they are, and much more. With disaggregated origin-destination data, planners can study, for instance, if a bus route connects some commuters to their jobs better than others, whether that’s because of home and work locations or because commuting hours don’t align with peak service times. Replica’s activity models also assist studies into the people who aren’t riding transit, offering insights into interventions that could boost ridership and equitable service at the same time.
Discover who benefits — and who doesn’t — from bike and pedestrian investments. Bike and pedestrian infrastructure offer great promise for transforming streets, neighborhoods, and cities, but building something isn’t enough to make a place more equitable. It’s not uncommon for investments in safer bike- and pedestrian-friendly streets to be concentrated in whiter, wealthier districts, or to serve higher-income residents better than the lower-income residents, who would benefit more from the chance to be less reliant on cars. The same data that reveals these inequities can also facilitate sustainability goals by helping planners see where people are taking short car trips that have potential to become transit, cycling, or walking trips with the right infrastructure.
El Paso, Texas, used Replica data for an analysis that showed a real connection between walkable places and pedestrian activity: Neighborhoods with higher walk scores see more walking, bolstering the notion that investing in pedestrian infrastructure can improve equity and accessibility by reducing the need to have a car.
Learn how commute times vary across demographic and geographic attributes. Last year, the Brookings Institution used Replica data from six U.S. metro areas to compile a report on travel behaviors. One key finding is that the average trip distance exceeds seven miles, meaning many people’s only choice for these trips is to travel by car. This level of car dependency contributes to the social, environmental, economic, and health impacts facing so many communities across the U.S., and the race and income variances in trip distances reflect patterns of racial and economic segregation.
Replica data revealed that trips starting in majority-minority suburban neighborhoods are more likely to cover longer distances than those originating from majority-minority neighborhoods in more centralized urban areas, highlighting the value of proximity in making transportation more affordable and making cities more accessible overall.
As the U.S. Department of Transportation works to fulfill President Joe Biden’s executive order on racial equity, it has the power to influence transportation equity efforts at public agencies across the country. The issue is too important to rely on assumptions, or to base decisions on decades-old data, especially considering how significantly the world has changed in just the past two years. Investing in new data tools can help agencies identify timely and meaningful actions while measuring progress toward equitable goals.