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84 Conclusions and Next StepsÂ In the United States, transit ridership overall has declined for six straight years. Bus ridership is at the lowest point since 1965 and rail ridership has decreased over the past few years, as well. There are many possible factors for this decline in ridership. A recent APTA report summed up many of the factors in four main areas: erosion of time competitiveness, reduced affinity, erosion of cost competitiveness, and external factors (APTA 2018). ï· Erosion of time competitiveness relates to increased congestion in cities from densification, delivery services, and TNCs, causing decreasing speed on shared right- of-way transit services such as traditional bus. Due to these decreasing speeds, additional service hours are needed just to maintain existing headways. ï· Reduced customer affinity and loyalty stems from changing populations that are less apt to purchase a monthly pass, because they telework or use multiple modes. ï· Cost competitiveness relates to the lower cost of auto ownership and inexpensive TNC fares. ï· External factors include parking availability and movement of major generators outside of dense areas. The recent decline in transit ridership is particularly worrisome because traditional factors of effecting transit ridership do not seem to be involved. According to data from the National Transit Database, transit agencies have increased bus service (vehicle revenue miles) by five percent between 2012 and 2016. Although our analysis found that amount of service provided was a strong predictor of both bus and rail transit ridership using 2012 data, the change in service levels was only a predictor of change in ridership in smaller cities or for dedicated right-of-way. In fact, we found that transit agencies had to increase service by 8-10% from 2012 to 2016 to expect unlinked passenger trips to remain unchanged. Meanwhile, urban population in the United States is at its highest point in recorded history (Census, 2012) and urban core areas have grown in population every year since 2006 (Frey, 2018). Although population is still a strong predictor of the level of transit ridership, especially for bus ridership in denser cities, our analysis found that population change and ridership change were entirely uncorrelated for bus and only somewhat correlated for rail. The health of the economy should also be encouraging people to make more transit trips. In 2017, unemployment levels in the United States were at their lowest level since the recession in 2009. A potential contributing factor to the decreasing transit ridership is the economic displacement of low-income earners from dense urban-centers to the suburbs (Florida, 2017). While cities are becoming denser, their populations have higher-incomes and more cars. Studies in Portland, OR, and Southern California have verified that low-income migration may be impacting transit ridership. In our analysis, 2012 proportion of zero vehicle households and transit ridership are not
85 strongly linked, but the 2012 to 2016 change in zero vehicle households and transit ridership are linked in the largest cities. The decreases in transit ridership found in the last four years were not only in the largest cities, but across the board. Nearly every transit agency investigated in the case studies had ridership increases through 2015, followed by steady decreases in ridership. Giving credence to the APTA time competitiveness factor, in every case study transit agency, average speeds are down or have remained the same. Commuter rail seems to be fairing better across the country and the transit agencies among the case studies are no different. Whatever is impacting bus transit ridership across the country does not have the same impact on the dedicated right-of-way longer distance commuter rail services. In an attempt to turn the declining transit ridership trend around, transit agencies have implemented new strategies. Transit agencies such as Houston and Baltimore are adding service and redesigning their networks to increase frequencies on their core routes and attract new riders. Others such as Portland, ME, and Spokane, WA, are adding service to attract certain populations. New pricing schemes and fare technologies are helping to incentivize riders and reduce the friction in transit fare purchasing. Transit agencies are implementing micro-transit pilots to provide a similar experience to TNCs or are partnering with TNCs to subsidize rides. Finally, transit agencies are using improvements to speed and reliability to improve service and ridership strategically, especially through more dedicated right-of-way that prioritizes transit over general traffic. Future Research The question that remains is how much these strategies can help mitigate and reverse the declines in transit ridership and how transit agencies can most efficiently implement these changes. Although there is a growing body of research on these factors, we still lack a comprehensive understanding of the extent to which various factors impact transit ridership and many of the strategies transit agencies are using to mitigate or reverse trends are not well understood from a ridership impact perspective. Population trends segmented by multiple factors such as age group, race and ethnicity, and income levels should be explored in greater detail to explain the impact of baby-boomer retirement and millennial transportation patterns, gentrification, and other similar migrations within a city. Further research is needed, especially at a disaggregate level that looks not at ridership on a city by city basis, but on a route by route and zone by zone basis using fare card and passenger counter data to understand where transit ridership is decreasing within a city and what external factors are impacting those decreases. Further research should assess not just ridership change on a yearly or even monthly basis, but should segment ridership into types of trips (long distance, short distance, commuter, offpeak) as sometimes ridership increases in one area can temporarily mask declines in another. Assessing individual trip behavior can also be a key to understanding
86 how ridership is changing. Additional work by TCRP is being conducted through TCRP A-43, âRecent Decline in Public Transportation Ridership: Analysis, Causes, and Responsesâ; and TCRP H-56, âRedesigning Public Transportation Networks for a New Mobility Futureâ. Both of these projects will conduct deeper dives into understanding the ridership question in a new mobility future.