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Pages 9-34

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From page 9...
... This chapter documents the state of the practice in travel demand forecasting for toll revenues. It begins by describing travel demand models (the basis of the toll road traffic forecasts)
From page 10...
... 11 Traditional origin–destination surveys are "revealed preference" surveys -- that is, they observe how people actually behave. However, these have proved limited as predictors of conditions that do not exist currently in a specific city: particularly the use of a new transit technology (notably, rail)
From page 11...
... nonmotorized modes (pedestrians and bicyclists)
From page 12...
... 13 trip generation and trip distribution typically are not modeled. The point is that the treatment of a (nominally)
From page 13...
... potential to generate "emergent behavior" (i.e., behavior is not explicitly "hard-wired" into the model, based on its calibration to conditions at a particular point in time)
From page 14...
... 15 speed restrictions, which arise from the above carfollowing logic, a vehicle's progress can also be delayed at traffic signals, ramp meters, queues, and/or other bottlenecks. The effects can be time-varying and may vary both spatially and temporally, which permits the replication of shock waves within the model.
From page 15...
... The MnPASS study used value-of-time data from an evaluation of the impacts of the Riverside Freeway (SR-91) tolled express lanes in Orange County, California.
From page 16...
... 17 collection bias (the increased likelihood of using a tolled facility, owing to the convenience associated with electronic toll collection)
From page 17...
... were also modeled to reflect the type of facility (i.e., the weekend model for areas of high recreational use)
From page 18...
... 19 traveler behavior (which may not be captured properly by the forecasting models or the data upon which they are based)
From page 19...
... Other authorities prepare simplified projections of annual revenues. These are based on an extrapolation of the previous year's (or years')
From page 20...
... 21 Authority/Facility Year of Opening Year 1 Year 2 Year 3 Year 4 Year 5 Florida's Turnpike Enterprise/Sawgrass Expressway (6) 1986 17.8% 23.4% 32.0% 37.1% 38.4% North Texas Tollway Authority/Dallas North Tollway (6)
From page 21...
... casts were revised. Other responses included revisions to the financial schedule, changes to the staging or timing of the project, or the implementation of annual updates and peer reviews.
From page 22...
... 23 • Location within well-developed parts of a large metropolitan area, with established traffic patterns. • Location within high-income corridor, with resultant high values of time.
From page 23...
... 2. Ramp-up risk, with recent methods based on the use of other operating facilities as proxies, but with "spotty" results.
From page 24...
... 25 Another exogenous event was the development of competing routes or the failure to anticipate network improvements such as feeder roads or highway interchanges. In some situations, noncompetition agreements have been developed that specify that other government agencies will not build competing facilities within a certain protected geographic area.
From page 25...
... Expressway toll road, also in Florida)
From page 26...
... 27 mate. Overall, respondents recommended collecting more or better data to improve travel demand forecasting results.
From page 27...
... develop over time in ways that were inconsistent with other evidence. [Other empirical studies have suggested that the value of time increases over time, but not proportionately with income levels (57)
From page 28...
... 29 Finally, one study noted the "growing body of empirical evidence that travelers value reliability as an important factor in their tripmaking decision." Reliability generally reflects the day-to-day variability in expected journey times, owing to nonrecurrent congestion such as incidents, weather, construction, and so on. Reliability is considered important in variablepriced HOT applications, where tolls are adjusted according to traffic volumes, to maintain a specified level of service.
From page 29...
... be observed. An inverse relationship between time savings and ramp-up has been observed, such that greater time savings appeared to correlate to a shorter ramp-up (5)
From page 30...
... 31 survey respondents, who noted the impact on the accuracy of forecasts of exogenous factors such as public or political inputs, land use, and network assumptions. For example, when uncertainties existed about whether a particular competing road would be constructed, it had been the practice to conservatively assume the competing road would be completed if it was expected to have a negative impact on the toll facility.
From page 31...
... • Sensitivity analysis while simultaneously varying toll road inputs simultaneously (the following list is a guide only, but it should be used as the minimum standard) : – Population growth, – Employment growth, – Personal income growth, – Toll elasticity by consumers, and – Acceleration of planned transportation network.
From page 32...
... 33 Optimism bias uplifts were introduced as methods of combating optimism bias in the decision-making process. They were established as a function of the level of risk that the British Department for Transport was willing to accept regarding cost overruns in transportation projects.
From page 33...
... but on a very limited basis and at a very small scale (5)
From page 34...
... 35 using traffic counts, origin–destination surveys, speed and/or travel time surveys, and land use inputs and network characteristics. The toll authority noted that it has recently received a rating upgrade on its revenue forecasts.

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