Abstract

Peaking on public transit—the concentration of ridership in peak times and directions into and out of central areas—has waxed in the U.S. over the past century, as public transit has lost more mode share at off-peak times, in off-peak directions, and among non-commute trips. A notable pre-pandemic manifestation of this chronic problem was on Bay Area Rapid Transit, the San Francisco Bay Area’s regional heavy rail system. While BART staved off an absolute ridership decline longer than most American transit operators in the mid-and late-2010s, it did so almost entirely due to peak gains in riders offsetting off-peak losses. As a result, the system experienced worsening passenger crowding at some times and places, expanding underutilization of capacity at many others, and the prospect of enormous expenditures to accommodate rising transbay passenger demand. To examine the factors driving transit use in the 2010s, we model peak and off-peak BART trips as a function of station area and system characteristics. We uniquely use origin-destination pairs as the unit of analysis in order to separately measure influences at both ends of the trip. We find that transfers and travel time most influence peak and off-peak BART ridership and that station-area employment and time competitiveness with driving particularly influence peak patronage. Over time in our models, the associations between ridership and transit travel time weakened, while the associations between ridership and transfers, employment, and time-competitiveness with driving grew stronger. In sum, we find that the peaking problem plaguing public transit systems for decades worsened in the years leading up to the pandemic—on this one nationally significant U.S. transit system, at least—which poses potentially substantial financial challenges in the years ahead.