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3 CHAPTER ONE INTRODUCTION BACKGROUND selected as case studies. A Transportation Research Infor- mation Services (TRIS) search was conducted to aid the lit- Traditional transit ridership forecasting relies on a four-step erature review. In addition, a message was posted on the travel demand forecasting model. This model has tradition- Travel Model Improvement Program (TMIP) e-mail list (see ally been used to compare and identify major travel invest- for additional information) ment policy choices. describing the synthesis project and requesting assistance. Several respondents suggested studies for inclusion in the lit- Because the traditional forecasting process is data and erature review. labor intensive, transit agencies have developed and applied other methods for transit demand forecasting and service The survey on transit ridership forecasting was designed to planning. Some methods may be used to estimate system- elicit information on methodologies in use in a variety of sit- wide ridership for budgeting purposes and others to estimate uations, satisfaction with these methods, and suggestions for the ridership impacts of new or revised services. These meth- improvements. A survey was sent to 45 selected transit agen- ods vary according to: cies in the United States and Canada. Each agency was con- tacted by e-mail or telephone before the surveys were sent to Geographic scale (from a single route or route segment ascertain interest and identify the correct recipient. Follow-up to the entire system), e-mails and telephone calls were placed approximately 6 and Scale of the service change (from a minor schedule 10 weeks after the original survey to encourage responses. adjustment to a major system restructuring), and Time frame for the ridership forecast (from one day to The selection of agencies for the sample was guided by the 10 years). existence of ongoing ridership forecasting activities, partici- pation in similar studies, random selection of additional agen- Given the wide variation in the purposes of a ridership cies to ensure adequate representation by size and location, forecast, it is not surprising that most transit agencies have and recommendations from other transit agencies. Initially, not developed a single formal methodology. From the 25 transit agencies were identified for inclusion in the sample. broader transit industry perspective, the transferability of a An additional 15 agencies were randomly selected from the particular methodology to other transit agencies is uncertain. National Transit Database (NTD) to make the sample more The end result is a widespread reliance on "back of the enve- representative in terms of geographic region and system size. lope" (improvised) methods, the accuracy of which depends At least 5% of agencies in each FTA district were included in on the knowledge and experience of the individual(s). Infor- the sample. Finally, respondents recommended five addi- mation on ridership forecasting approaches that bridges the tional agencies for inclusion in the sample, bringing the total gap between the back of the envelope and the four-step travel to 45 transit agencies. Thirty-six agencies completed the sur- demand model would be very useful for transit agencies. veys, a response rate of 80%. Technological changes have affected the forecasting Table 1 presents the distribution of responding agencies process. One example is the increasing use of automated pas- by size. senger counters (APCs) that enhance the quantity, reliability, and level of detail of ridership data. Another is the prevalence Table 2 shows the distribution of responding agencies by of geographic information system (GIS) tools that greatly FTA region. Figure 1 is a map of FTA regions. simplify the process of summarizing demographic and employment data and relate these spatially to transit routes ORGANIZATION OF REPORT or route segments. Following this introductory chapter, chapter two summarizes METHODOLOGY the findings of the literature review. Chapter three, the first of two chapters to present the results of the survey, focuses This synthesis included a literature review, a survey of tran- on forecasting methodologies, resource requirements, data sit agencies, and telephone interviews with six agencies inputs, and organizational issues. In the process of survey

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4 TABLE 1 SAMPLE AND RESPONDING TRANSIT AGENCIES BY SIZE No. of Vehicles Operated in No. of Agencies Maximum Service Responding 150 5 51100 4 101250 11 251500 3 501+ 13 FIGURE 1 Map of FTA regions. To tal 36 ship under each scenario. This chapter includes agency responses. TABLE 2 SAMPLE AND RESPONDING TRANSIT AGENCIES BY FTA REGION Chapter four discusses the responding agencies' assess- No. of ment of their own forecasting methods. This chapter summa- Agencies rizes perceptions of data reliability and accuracy, satisfaction FTA Region Responding with current methodologies, desired improvements, lessons I 2 learned, and advice for other transit agencies. II 5 III 2 IV 4 Chapter five reports detailed findings from each of the six V 3 case studies. Agencies were selected for the case studies for VI 3 VII 2 a variety of reasons. Some approaches can be characterized VIII 1 as "best practices." One case study presented a setting in IX 9 which forecasting methodologies are not considered to be X 3 Canada 2 necessary. All six show a thoughtful response to the issues Total 36 posed by ridership forecasting. Chapter six summarizes the findings, presents conclusions development, the wide variety of circumstances that could from this synthesis project, and offers suggestions for further generate the need for a ridership forecast became apparent. research. Findings from the surveys and particularly the case To address this issue, the survey provided seven specific studies provide an assessment of strengths and weaknesses scenarios and asked how the agency would forecast rider- in current methods and likely future directions.