Transit Equity Is Not Only About Which Communities Transit Serves - It's Also About When

The typical starting point for transit improvement efforts is to understand underlying demand. This is most often determined using population and employment density because transit works best in dense places. However, density alone does not take into account that different populations use transit at different rates. To reflect this, Nelson\Nygaard has developed a process that more accurately measures transit demand. This process makes transit service more equitable by more accurately identifying areas with greater needs. It also helps make service more productive because ridership will be higher where demand is higher.

Four factors, in particular, have strong influences on transit demand:

• Race and ethnicity: People of color use transit more, and non-Hispanic white people use transit less.
• Vehicle ownership: Members of households with no or few cars use transit more, and those with many cars use transit less.
• Country of origin: People born outside the United States are usually more likely to ride transit than those native born.
• Household income: People from lower-income households are more likely to use transit, and people from higher-income households use transit less.

_{In Fort Worth, high-transit-propensity groups tend to live in the southeastern quadrant of the city, with some isolated high-transit-propensity groups to the west and north-west. Adjusting the population by transit propensity results in these areas having a much higher demand for transit than by population density alone. Areas in the northern part of the map are home to residents less likely to take transit, and their demand for transit is lower than density alone would indicate.}

By understanding how people in these different demographic groups use transit relative to the “average resident,” we can adjust the raw population density-related demand up and down to much better reflect underlying demand. Also, rather than mapping every demographic variable separately, we can create one map that shows where concentrations of transit-dependent residents live.

‍The Off-Peak Service Gap

Transit agencies have traditionally provided more service during peak periods than at other times of day. In Greater Boston in 2018, 51% of workers left for work in the two hour period between 7 and 9 a.m., and 49% left in the other 22 hours. The MBTA’s schedules reflected those patterns with much more service in the peak periods and much less during off-peak periods. However, similar to transit propensity, different demographic groups vary broadly from the “average.” In Everett and Chelsea, two communities north of Boston with high proportions of low-income residents, residents of color, and foreign-born residents, only about a third of workers leave for work during the a.m. peak, where as in Needham, a wealthy suburb, nearly two-thirds of workers leave during a.m. peak. The pandemic has helped to reveal that peak period demand is not the same across different types of workers, and when office workers stay home, transit ridership patterns look very different. Demand has flattened to the point where demand in the peak is only slightly higher than during the rest of the day, and many of those who are riding are essential workers.“Peak periods” for essential workers look more like rolling hills.

How and when demand returns is still speculative. However, many expect that people currently working from home will continue to do so part of the time. This would mean future demand by time of day will be flatter than pre-pandemic demand. There is also now a much greater focus on convenience and, in particular, the development of frequent transit networks that provide frequent service throughout the day.

Due to financial problems, transit systems often provide the minimum amount of service needed to meet demand, and 49% of demand spread over 22 hours has meant that 49% of workers are provided with infrequent service. The development of frequent transit networks—and more frequent off-peak service on other routes as well—not only makes service more convenient for all, but in particular for essential workers and others who rely on transit the most.

The times when people travel to and from work also vary by geography and demographics. Again, using Greater Boston as an example, communities with higher proportions of residents of color, low-income residents, and residents born outside of the United States have much higher numbers of workers who commute outside of traditional peak hours. These communities have also maintained some of the highest ridership rates throughout the pandemic, as they are the places where many essential workers live. To provide equitable service, it is just as essential to match service with when residents need it as it is to the places where they need it.

Many transit agencies are now putting equity at the forefront of their planning efforts. To create an equitable transit system, the first step is to understand how needs vary—and then do what it takes to match service to those needs.

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