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19 Neither overly simple nor overly complex New technologies have had an effect on agencies' fore- approaches work. casting methods. APCs and farebox upgrades or auto- GIS as data integration tool simplifies data manage- mated fare collection were most frequently mentioned ment. among new technologies, but several off-vehicle tech- Transferability: Institute of Transportation Engineers nologies were also noted. Improvements in data accu- trip generation rates are very accurate; our mode split racy, reliability, and level of detail are among the primary is very similar across our service area. effects of new technologies. Many agencies also cite Take the time to develop patronage forecasts. improvements in data availability and integration of data Interpretation and presentation in lay terms is as from different sources. important as the forecasts themselves. The question regarding satisfaction with current fore- Admitting that forecasts were wrong and finding out casting methods yielded very interesting results: why is the best teacher. roughly one-third of responding agencies are satisfied, one-third are partially satisfied, and one-third are not satisfied with current forecasting methods. Quality and SUMMARY availability of input data and accuracy of the forecasts are the most pressing concerns. This chapter has described agency assessments of ridership Input data and methodology were the most frequently forecasting methods. Findings include: mentioned aspects of ridership forecasting procedures that transit agencies would like to change. Agencies Results regarding agency satisfaction with the reliability report a need for greater data availability, more current of input data are mixed, with 44% of respondents indi- data, and data at a more detailed level. Methodology cating general but not complete satisfaction. The greatest needs were more diverse, reflecting that various agencies reliability concerns center on ridership data; however, the are at different stages regarding forecasting methods. timeliness and level of detail for origin/destination and Among the specific responses were greater sophistica- demographic data are also issues. tion, more consistency, and easier to apply models. Nearly all agencies measure the reliability and value of Roughly half of all survey respondents shared lessons their forecasting methodologies through a comparison learned from the process of developing and using rider- of actual ridership with ridership forecasts. Board ship forecasting methodologies. The most commonly understanding and approval is also a factor for 27% of mentioned lessons included interpreting results cau- respondents. tiously and simplifying the approach to ridership fore- A majority of responding agencies do not have the opti- casting. Responding agencies made several other mal amount of data available for forecasting ridership. important and useful observations. The most common concern is availability of ridership data below the route level (by route segment or stop), The following chapter describes findings from six case and many agencies anticipate that APC implementation studies that explore issues related to ridership forecasting in will solve this. greater detail.