Track outcomes of the transportation system for people who depend on transit and people facing marginalization wherever they live in the region, and for neighborhoods with a high concentration of residents who depend on transit or who face marginalization.
To measure progress towards equitable transit, agencies must define and measure outcomes for people and the communities in which they live and work. Transit agencies need at least two types of metrics:
- Place- or neighborhood-focused measures show how the benefits and harms of transportation accrue to areas with many residents of color or residents with low incomes. Neighborhood-focused measures often show outcomes for defined areas of need (the definition varies by agency but may be based on factors such as the proportion of residents who have low incomes, are not white, or lack access to a vehicle) against the region as a whole. An example of a neighborhood-focused measure is, “How reliable is bus service in racially concentrated areas of poverty?”
- Person-focused measures show how benefits and harms of transportation accrue to people of certain identities, aggregating across residential locations. An example of a person-focused measure is, “How reliable is bus service for the average Black bus commuter?”
Place- or neighborhood-focused measures
Place- or neighborhood-focused measures assess transportation outcomes in areas where many residents are BIPOC or have low incomes. These areas tend to have faced disinvestment historically and have concentrated need for investment now; neighborhood-focused measures help make the case for equitable, place-based investments.
Several transit agencies define areas of need using a mix of Census, transit agency, and other data. For example, the San Francisco Municipal Transportation Authority has defined eight “equity neighborhoods” based on income, private vehicle ownership, race, and ethnicity. According to agency policy, service should improve in these neighborhoods at least as much as in the system as a whole. SFMTA issues a biannual report showing how transit performance has changed in those neighborhoods and identifying improvements to make (see example below).
Neighborhood-Focused Metrics from SFMTA Muni Equity Service Strategy:
SFMTA’s Muni Equity Service Strategy commits the agency to “assess Muni service performance in select low income and minority neighborhoods, identify major Muni transit-related challenges impacting selected neighborhoods with community stakeholder outreach, and develop strategies to address the major challenges. … SFMTA shall develop performance targets for each strategy based on peer Muni route performance and track progress compared to baseline conditions, performance targets, and year-over-year progress.
“Performance metrics will include:
- On-Time Performance
- Service Gaps
- Crowding (also serves as a proxy for pass-ups)
- Capacity Utilization
- Travel Times to/from key destinations such as the nearest grocery store, nearest medical facility, City College, downtown, and nearest major park
- Customer satisfaction information
Metrics will include data by time of day (including midday and late evening). Where available, data will be evaluated for conditions within the neighborhood, as well as the route as a whole.”
The SFMTA prioritizes service improvements in the eight equity neighborhoods, as well as on 15 routes with a large proportion of riders with disabilities and senior citizens. This slide from a 2018 presentation shows how the agency works to identify needs in equity neighborhoods and make service improvements accordingly.
Other agencies that have used neighborhood-based equity measures to guide capital investments or service decisions include Metro Transit in Minneapolis-St. Paul and TriMet in Portland, Oregon. Geographic measures can also assess harms. For example, TriMet measures whether older, more-polluting buses are disproportionately located in equity neighborhoods. (The Metro Transit and TriMet examples are case studies later in this report.)
Transit investments outside of equity neighborhoods can improve outcomes within those neighborhoods. For example, a bus lane or rail tunnel in a congested downtown area can improve travel times for riders who don’t live downtown, but travel through it.
Person-focused measures show transportation outcomes for groups of people, regardless of where they live. Person-focused measures are necessary to design and evaluate programs intended to improve outcomes for marginalized groups of people. Relying only on neighborhood-focused metrics obscures the needs of, for example, a Black family living in a predominantly white neighborhood.
Person- and neighborhood-focused measures can be calculated from the same data sources, but person-focused measures require an extra step to rearrange spatial data into population groups. Because of their simpler methodology, neighborhood-focused measures are sometimes used instead of person-focused measures, even if the latter is more appropriate.
One common set of person-focused measures are “access to opportunity” metrics, which calculate how many jobs (or how many high-quality jobs), grocery stores, parks, or other destinations a person can reach on public transit in a certain amount of time, or how many people have access to frequent transit service. Miami-Dade County analyzed its bus network redesign by measuring the number of jobs that the average person, average person in poverty, average person of color, and average person without a vehicle could reach on transit, before and after the redesign.
Travel diaries and Census journey-to-work data capture individual travel behavior and are common sources for person-focused measures. But they are biased toward commuting trips and long trips, a segment of all trips that people take and one in which wealthier people are overrepresented. Anonymized location data generated from smartphone apps captures trips of all purposes and distances. These location-based services (LBS) datasets can be merged with demographic data to measure how different groups of people travel, more completely and accurately than common sources. (However, there are concerns that they underrepresent older adults and non-English speakers who are less likely to have smartphones.) LBS datasets have not yet been applied to create person-focused equity measures; however both the Massachusetts Bay Transportation Authority and Los Angeles Metro have created other measures with LBS datasets (these examples are discussed in the case studies).
Person-focused measures can convey impacts that neighborhood-focused metrics cannot. For example, while neighborhood-focused metrics can evaluate whether a new light-rail line improves transit access to jobs along the route, they don’t capture whether residents with low incomes are displaced as the area becomes desirable to more affluent people. Only person-focused measures can determine whether people with low incomes enjoy better access thanks to the new light-rail service.
Person-focused measures also capture the needs of communities of people that don’t map onto a defined geography. For example, focus groups conducted by the Portland Bureau of Transportation in Albina, a historically Black but quickly gentrifying neighborhood, convinced the department to move a planned bike lane off a street where many Black cultural institutions were sited. Planners learned that many Black Portlanders had been displaced from Albina, but continued to use (and drive to) the cultural institutions on the street. Qualitative engagement led planners to recognize the presence of a diaspora community.