TCRP A-43: Recent Decline in Public Transportation Ridership: Analysis, Causes, Responses

Grants and Contracts Details


The objectives of this research are three-fold: 1. To understand the factors contributing to the recent decline in transit ridership in the United States and quantify the relative contribution of each. 2. To identify strategies to mitigate or reverse those declines and to evaluate the effectiveness of those strategies. 3. To develop recommendations for how public transportation agencies can respond to the ridership challenges they are currently facing. As discussed in the project understanding, a mix of factors are contributing to recent ridership trends, several of which will push ridership in competing directions. Therefore, it is insufficient to address the topic with only an exploratory data analysis or through a qualitative assessment. Such exercises quickly become speculative, as can be found in much of the literature on the topic over the past few years. Instead, as we propose here, it is necessary to combine detailed data with robust statistical methods to separate out these competing factors. However, we propose to go one step further to aid in decision-making by transit agencies and their partners by translating the results of those technical analyses into a set of policy-level tables that show the relative contribution of each factor to the total ridership change. We propose to do this in a two-phase, top-down approach that considers ridership changes at the system level, the route level, and the stop level. This will let us both consider the diversity of transit systems in the United States and take advantage of more detailed data that we have assembled for specific cities. Phase I will be centered on a multi-city analysis in which we develop longitudinal models of the change in system-level transit ridership by mode across many cities. This high-level analysis will ensure that the trends we are capturing are broadly applicable across the nation and builds directly from work we have already started. Phase I also includes the development of specific, testable hypotheses related to the contributors to change, and the identification of response strategies to be tested in Phase II. In Phase II, we will dive deeper into both the causes and the strategies through a series of case studies for specific cities. These deep dives will allow us to: 1. Analyze the problem using more detailed ridership data that have already assembled, allowing us to capture differing trends at the route level and the stop level; 2. Introduce additional data that are not available for all cities, including unique data sets we have acquired or are in the process of acquiring showing the spatially detailed trips on Transportation Network Company (TNC) trips in cities of multiple sizes and transit landscapes (including Boston, New York, San Francisco, Portland, Atlanta, and others); 3. Explore specific success stories, such as Seattle, where agencies have managed to buck the trend of declining ridership; and 4. Test the proposed mitigation strategies using our data-driven simulation tool, CityCast. System-level Route-level Stop-level Level of
Effective start/end date1/17/193/31/21


  • Georgia Institute of Technology: $91,576.00


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