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31 ORGANIZATIONAL ISSUES The VIA Metropolitan Transit (San Antonio) case study provides an example of a traditional approach that The planning department is the most likely home for the relies heavily on professional judgment and an under- forecasting function within a transit agency. However, standing gained through experience of the factors con- it is not unusual for multiple departments to be involved tributing to transit ridership. in different levels of ridership forecasting. The Regional Transit District (RTD) (Denver) case Responsibility for ridership forecasting is more likely study shows how new technologies such as APCs, inte- to be part of general duties for all but major changes. grated software, and GIS can improve the quantity and A range of estimates were given for the time and effort quality of ridership and other data, provide new meth- required to prepare ridership forecasts. Simple or short- ods for analyzing and forecasting ridership, and greatly range forecasts can generally be completed in 3 days or enhance its ability to communicate results to stake- less. A wide time range in long-range forecasts reflects holders. At the same time, RTD relies on research proj- the method used; a trend line analysis takes much less ects such as TCRP Report 95 to provide invaluable time than a four-step model run. documentation of experience elsewhere. Ridership forecasts are nearly always distributed and The Greater Richmond Transit Company (GRTC) case used internally. A majority of responding agencies also study shows that there may not be a real need for a rider- share the forecasts with their boards. ship forecasting methodology at all transit agencies. The decision-making process at many small and mid-sized agencies is driven more by politics and funding availabil- RELIABILITY AND ACCURACY ity than by ridership analysis. Although many agencies Nearly all agencies measure the reliability and value of can see the value of employing a forecasting methodol- their forecasting methodologies through a comparison ogy, it may not rank highly in terms of current needs. of actual ridership with ridership forecasts. Board The Metropolitan Transit AuthorityNew York City understanding and approval is also a factor for 27% of Transit (MTANYC) case study shows how application respondents. of new data collection techniques (automated fare col- The question regarding satisfaction with current fore- lection) and GIS analytical tools can improve ridership casting methods yielded interesting results. Roughly forecasting procedures. Successful exploration of new one-third of responding agencies are satisfied, one-third analytical methods (such as inferred origins and desti- are partially satisfied, and one-third are not satisfied nations) as ridership data become more reliable is an with current forecasting methods. Quality and avail- important finding that can be applied elsewhere. ability of input data and accuracy of the forecasts are Encouraging interaction between modelers and end- the most pressing concerns. users through organizational structure and location of Input data and methodology were the most frequently the departments can ultimately result in model mentioned aspects of ridership forecasting procedures improvements and greatly increases the likelihood of its that transit agencies would like to change. Agencies being trusted and used on a consistent basis. reported a need for greater data availability, more cur- The Orange County Transportation Authority (OCTA) rent data, and data at a finer level. Methodology needs case study indicates that GIS programs, formal model- were more diverse, because various agencies are at dif- ing efforts, use of elasticities, and professional judgment ferent stages regarding forecasting methods. Among can together provide a menu of ridership forecasting the specific responses were greater sophistication, more methodologies for use as appropriate. The various consistency, and easier to apply models. departments that require ridership forecasts are com- fortable with the methodologies and confident in the results. Additional work is ongoing to enhance accuracy LESSONS LEARNED AND CASE STUDY RESULTS and simplify the use of these methodologies; however, OCTA has achieved a high level of confidence in its rid- Approximately half of all survey respondents shared ership forecasts in a wide variety of situations. lessons learned from the process of developing and The Tri-County Metropolitan District of Oregon using ridership forecasting methodologies. The most (TriMet) case study provides an example of a ridership commonly mentioned included interpreting results cau- forecasting model in use at a transit agency. It is note- tiously and simplifying the approach to ridership fore- worthy that TriMet's first choice of methodology for casting. Responding agencies made several other incremental service changes is similar-route analysis, important and useful observations. but the model is useful in addressing unique situations. Each of the case study agencies was very different in TriMet also relies heavily on service headway elastici- terms of approach to ridership forecasting, response to ties to assess the impact of changes in frequency. local issues and concerns, and use of various methods TriMet believes that its model and approach could be and techniques. All showed a thoughtful response to the used at other transit agencies once calibrated with that issues posed by ridership forecasting. agency's ridership data.