Recent Decline in Public Transportation Ridership: Analysis, Causes, and Responses (2022)

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1   Pre-pandemic Transit Ridership The coronavirus disease 2019 (COVID-19) pandemic has dramatically affected all segments of economies across the globe, and mobility providers have been among the most affected by the stay-at-home mandates. Across cities, there have been significant declines in rail ridership compared to pre-pandemic levels, as rail modes are often used by workers who are more likely to have telework options. Bus ridership has also significantly decreased, though somewhat less than rail ridership since much of the lower-income and critical workforce populations that buses often serve continued riding transit out of necessity. However, transit systems in the United States were already facing challenges prior to the pandemic with respect to ridership: Transit ridership declined 14% to 15% nationwide between 2012 and 2018. Buses were the most affected with the lowest ridership levels since at least the 1970s, and even heavy rail declined starting in 2015. As transit ridership declines, agencies lose fare revenue, which often results in reductions in service to meet budgets, which further results in losses in ridership—thus creating a downward spiral. The causes of these pre-pandemic ridership losses were multiple and complex. As a result, TCRP initiated this research study to provide a deep-dive exploration of the ridership losses already being experienced by transit systems. This study was initiated before the pandemic and uses pre-pandemic data for its analyses. The objectives of the research are threefold: 1. To understand the factors contributing to the pre-pandemic decline in transit ridership in the United States and quantify the relative contribution of each factor, 2. To identify strategies to mitigate or reverse those declines and to evaluate the effective- ness of those strategies, and 3. To develop recommendations for how public transportation agencies can respond to the ridership challenges they have been facing both pre- and post-pandemic. To accomplish these objectives, the researchers first conducted a thorough literature review and developed ridership change hypotheses. They then combined detailed data with robust statistical methods in a top-down approach that considered ridership changes at the system level, the route level, and the stop level. Finally, they conducted a future strategies analysis by simulating two transit networks. The combination of these methods has allowed the research team to both consider the diversity of transit systems in the United States and take advantage of more detailed data assembled for specific cities. S U M M A R Y Recent Decline in Public Transportation Ridership: Analysis, Causes, and Responses

2 Recent Decline in Public Transportation Ridership: Analysis, Causes, and Responses Explaining Transit Ridership Declines Through the literature review shown in Chapter 2, four categories of factors and strate- gies for transit ridership change were identified, broken into the intersection of internal and external factors and traditional and emerging factors. Internal factors are those that transit agencies can control, while external factors are those that impact transit agencies but over which they have little control. Traditional factors are those that have long been shown to impact transit ridership, while emerging factors are more recent phenomena. Combining these two groups of factors gives us the following four categories: • “Internal traditional” includes factors such as service quantity and quality, fares, and speed and reliability; • “Internal emerging” includes factors such as restructuring transit networks, fare innovation and real-time technology, new on-demand services, and dedicated right-of-way; • “External traditional” includes factors such as population and employment, demographics, car ownership, gas prices, and transportation demand management (TDM); and • “External emerging” includes factors such as telework and teleshopping, gentrification, and new transportation services. The existing literature identifies the important factors and the likely direction of each, but it is clear that a mix of factors are contributing to recent transit ridership trends, pushing transit ridership in competing directions. To separate the effects of each of these factors, Chapter 3 presents the multicity evaluation of ridership change, which developed longi- tudinal models of the change in system-level transit ridership by mode across many cities. This high-level analysis ensures that the trends being captured are broadly applicable across the nation. The models use National Transit Database (NTD) ridership data, U.S. Census Bureau data, and other data sources to test some of the hypotheses about ridership change for both bus and rail. Overall, two sets of factors pushed to increase transit ridership from 2012 to 2018: • More service. Transit operators are providing more bus and rail service. These service additions result in a net bus ridership increase ranging from 3% to 5% depending on the size of the metro area. Rail service increases are associated with ridership gains of 10% to 18%. • Land use. Land use affects transit ridership in terms of total population and employment growth and in terms of how centralized that growth is. Metro areas have grown between 6% and 8% in population and employment, pushing up ridership. However, in many cases, that growth is becoming less centralized—pushing ridership down—so that the combined effect of land use changes is a less than 2% increase in ridership. The causes of net transit ridership decline between 2012 and 2018 came from a combina- tion of four main factors. Together, these factors more than offset the factors above that pushed ridership up over this period. These factors are the following: • Income and household characteristics. Higher incomes, higher rates of car ownership, and an increase in the percent of people working at home contributed a net ridership decline of about 2% for bus and rail. • Bus and rail travel became more expensive. Average bus fares increased across most metro area sizes. Average rail fares increased between 7% and 13%, depending on the size of the metro area. The result is net ridership declines of 0% to 4%. • Driving became less expensive. Average gas prices decreased by about 30% over this period, contributing to about a 4% reduction in bus and rail ridership. • New modes compete with bus and rail. The model results suggest that ride-hailing is the biggest contributor to dropping bus ridership between 2012 and 2018, resulting in net

Summary 3   decreases of between 10% and 14%. The effect of ride-hailing on rail ridership in larger metro areas is much smaller, but the effect in the mid-sized metro areas is similar to its effect on buses. Bike sharing and e-scooters have a much smaller impact, less than or about 1%. Transit Agency Strategies and Ridership Factors Although the system-level analysis has identified some important factors in ridership declines, many factors and strategies cannot be assessed at the national level due to inconsis- tencies in data from transit agency to transit agency or due to phenomena that are occurring at a more disaggregate level. The second phase of the research used more detailed data from specific cities to conduct deep dives into both the causes of ridership change and strategies to reverse declines. The results of this detailed route- and stop-level analysis of various critical factors and simulation of future strategies found several key things: • Transit priority can increase transit ridership. The case studies in Minneapolis and St. Paul, Minnesota (Chapter 6), and Cleveland, Ohio (Chapter 9), showed that high- quality light rail transit (LRT) and bus rapid transit (BRT) can increase ridership sub- stantially, even with limited service increases. The future strategies analysis showed that bus-only lanes can be even more effective than increases in service at increasing transit ridership. • Fare policies and discounts can increase transit ridership. The case study in Topeka, Kansas (Chapter 8), showed that strategic fare discounts can increase transit ridership. Fare-free promotions for kids in the summer, seniors, and veterans can increase the use of transit. • Micromobility has limited impacts on transit ridership. The case study in Louisville, Kentucky (Chapter 7), showed that e-scooters had limited—if any—impact on local bus ridership and may have even slightly increased express bus ridership. Transit agencies can consider micromobility partnerships to address first-mile/last-mile connectivity issues. • Condensing service can increase transit ridership. The system-level analysis (Chap- ter 3) showed that transit ridership has been increased through not only added service but also bus network redesigns. This was reinforced though a future strategy analysis (Chapter 10), which showed the potential to increase transit ridership without major budget increases by reallocating existing service. • Pre-COVID, peak-hour service was the most productive. Analysis across four agencies (Chapter 4) showed that a.m. and p.m. peak ridership was declining the least and night- time ridership was declining the most. The most productive transit service (ridership per vehicle hour) was weekday peak hours. At the same time, nighttime ridership was found to be the most sensitive to changes in frequency. Putting together both phases of the project led to the five recommended strategies presented in Chapter 11: • Rethink mission, service standards, metrics, and service delivery. The research in this report has shown that prior to the COVID pandemic, transit ridership was peaking, with a.m. and p.m. peak ridership declining the least while weekday night and weekend night ridership declined the most; this was likely caused in part by the competition offered by ride-hailing services. How new COVID trends will interact with previous trends repre- sents a major challenge for transit agencies as they try to plan for the future and reposi- tion their mission and services. In light of this, transit agencies will need to rethink their mission, their service standards, the metrics they use to measure success, and their service delivery options.

4 Recent Decline in Public Transportation Ridership: Analysis, Causes, and Responses • Redesign fare policy. Fare policy is typically within the control of the transit agency. The research in this report on pre-COVID trends confirms the positive impact on ridership that can be obtained from the implementation of fare discounts. At the same time, recent developments during the pandemic suggest that patterns may be significantly altered in the future with more teleworking and less regular commuting to downtown cores, which suggests that a review of fare policy may be required. • Give transit priority. The research in this report has shown that giving transit priority can significantly increase transit ridership. Transit priority helps to increase average speeds, reduce travel times, and increase service reliability, which all contribute to making the transit service more attractive to potential riders. There is an array of increasingly com- plex methods and means to improve transit priority, including physical priority, transit signal priority (TSP), BRT, and LRT. Transit agencies can only implement physical priority measures and TSP in cooperation with the traffic engineers who manage traffic signals and the design and operation of streets, while the design and implementation of BRT and LRT systems are by their nature major, complex, and multiyear undertakings. • Consider partnerships with shared-use mobility providers carefully. Many experts have suggested that transit agencies should develop partnerships with new, shared-use mobility providers, such as ride-hailing, microtransit, car-sharing, and micromobility (e.g., bike sharing, e-scooter) providers, in an effort to offer a broader array of services that might encourage people to not use their personal automobile. However, the research shows that transit agencies need to consider such partnerships with care since these new services can sometimes be competitors to transit, while others may serve a complementary role. • Encourage transit-oriented density. The research in this report shows that regions where density increased in the areas accessible by transit experienced growth in transit ridership. The challenge is that density is defined by metropolitan and municipal planning policies and by the practical zoning regulations put in place by municipalities, none of which are under the control of transit agencies. Nonetheless, transit agencies can play an important role in encouraging transit-oriented density. Future Impacts on Transit Ridership As society moves to the “new normal” of a post-pandemic world, researchers are still trying to understand what longer-term impacts the pandemic might have on mobility, and public transit in particular. Although this research was based on pre-pandemic data, the findings from this detailed assessment of factors affecting transit ridership suggest a few key insights for the future: • Telecommuting impacts on transit will likely continue. Even before the pandemic, telecommuting was impacting transit. During the pandemic, these impacts have been substantial and necessary. However, as the pandemic subsides, it is likely that many firms will retain some telecommuting practices; this will likely change expectations from the model of five days per week at the office and reduce the gap between peak hours and off- peak demand. • Population density may continue to decline. As with telecommuting, even before the pandemic, population densities were decreasing; this has offset increases in transit rider- ship being seen from population increases. It remains to be seen how the public will react in the longer term, but with more flexibility in job locations comes more flexibility in living locations and a need for greater space in the home. • Low gas prices hurt transit ridership. During the pandemic, oil producers could not give their product away. As traffic congestion has increased, gas prices have as well, but gas prices have generally stayed very low. If lower demand is sustained, it could continue

Summary 5   to keep gas prices low, making driving a much cheaper option and adversely impacting transit ridership. • Potential for higher transit fares. Similarly, driving may stay cheap compared to transit if agencies are forced to raise fares to begin recovering their financial losses caused by the pandemic. The key to making transit affordable is high ridership on a per vehicle hour basis. With low ridership per vehicle hour, transit has to be subsidized to keep it affordable. • Impact on new modes is unknown. Ride-hailing services also require sharing space, similar to transit. Although ride-hailing use was growing rapidly before the pandemic, its future trajectory and resulting impact on transit remains to be seen. These future impacts point even more toward the successful strategies that agencies have been pursuing before the pandemic as well as new strategies presented here. This will allow the transit industry to continue to fulfill its twin mission—both to respectfully serve those who rely on transit on a day-to-day basis, through more emphasis on equity of accessibility and service, and to efficiently provide mobility in congested areas. Although the coming years may continue to be challenging, the transit industry is filled with champions who are eager to rise to the task of creating a more resilient and sustainable transportation system.