Metropolitan Travel Forecasting Current Practice and Future Direction -- Special Report 288 (2007) / Chapter Skim
Currently Skimming:
5 Shortcomings of Current Forecasting Processes
5 Shortcomings of Current Forecasting Processes
Pages 65-89
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 65... ...
Travel forecasting introduces a reasonbased rigor into the planning process that would otherwise be lacking. Given the inherent uncertainty in knowing the future, it is imperative that forecasting models themselves not introduce undue additional uncertainty.
|
From page 66... ...
. • A report of the National Cooperative Highway Research Program reviews the current state of the art for analyzing transportation control measures and concludes that "serious reservations exist concerning the accuracy of these results, the robustness of the underlying data, and whether the correct set of variables are captured in the model systems." The report recommends a new modeling framework consisting of the following modules: disaggregate and activity-based demand, household sample enumeration, incremental analysis, traffic microsimulation, and household travel survey data with stated prefer ence data to support policy analysis (Cambridge Systematics 2001)
|
From page 67... ...
In particular, the current widely used four-step metropolitan travel demand forecasting process cannot adequately characterize the following (without the use of off-model adjustments) : • Road pricing; • Time-specific policies, such as parking, work schedules, and scheduling of truck deliveries; • Hourly speeds or traffic volumes; • Improvements in traffic operations; • Improvements or policies addressing freight movement; • Nonmotorized travel; • Peak spreading and highly congested networks; or • Goods movement.
|
From page 68... ...
Two examples illustrate this point -- road pricing and goods movement. Road Pricing The summary of a 2005 Expert Forum on Road Pricing and Travel Demand Modeling notes that "the four-step modeling system does not capture behav ioral responses to pricing options because pricing has dynamic, interactive effects that cannot be accommodated in a linear, static modeling system" (Schofer 2006, 10)
|
From page 69... ...
, but FitchRatings also points to "the use of regional travel demand models intended for other planning purposes and not necessarily appropriate for use to support the issuance of toll road debt" (FitchRatings 2003, 2)
|
From page 70... ...
Implementing this approach could require forecasting demand and revenue for an existing free way segment that is to be reconstructed, expanded, and subsequently operated as a toll road. As noted by Spear, however, "Virtually all of the road pricing models implemented to date have been used to analyze the travel demand and revenue impacts of static tolls (i.e., toll charges that remain constant over a fixed time period)
|
From page 71... ...
Without a better understanding of freight activity and models based on data that reflect real-world logistics and distribution systems, planners cannot begin to assess, for example, how the performance of the transportation system would change if truck deliveries were limited to off-peak delivery times. Failure to Deal with Uncertainty in Model Estimates Most travel forecasting models produce a single answer, although the model is estimated, calibrated, and validated on the basis of data sets that are subject to many sources of error and uncertainty.
|
From page 72... ...
The regional travel demand models in use today can treat such variation only in an aggregate estimate, although some studies have used detailed simulation procedures to augment the forecasts derived from these models. One barrier to including reliability as a variable in road pricing models is that traditional four-step travel demand models are designed structurally to work with average or mean values (e.g., average daily or average peak period travel volume)
|
From page 73... ...
The U.S. census provides some independent information about the distribution pattern of work travel, but other than results of household travel surveys, there are no data against which nonwork trip distributions can be validated.
|
From page 74... ...
Reports of allocation of "forecasts by negotiation" are common. Many agencies have begun to include in their model sets factors intended to reflect the influence of subarea development patterns, including density, activity mix, and design, on trip generation, distribution, and mode share.
|
From page 75... ...
Use of Models Without Regard for Their Limitations As noted earlier, travel models were originally developed for macro-scale regional planning. With many adjustments and new components, they have been adapted for the study of many other issues, including transit station boardings and projections of regional emissions.
|
From page 76... ...
With few exceptions, travel forecasting procedures make use of data that are developed independently, often with no input from or feedback to transportation system attributes. These data -- forecasts of population, house holds, and employment, both in total magnitude and as allocated to specific geographic subareas -- are significant drivers of travel forecasts.
|
From page 77... ...
One needs to be careful to separate errors in variables input to a travel model from the model itself. Errors in demographic forecasts can lead to the incorrect location of trip origins and destinations, creating significant orientation errors in trip distribution and accessibility anomalies in transit forecasting.
|
From page 78... ...
Forecast 4,202 1,556 2,397 Actual 4,069 1,543 2,654 Difference 133 13 −257 % Difference 3.3% 0.8% −9.7% Portland, Oregon Forecast 1,499 588 803 Actual 1,789 697 929 Difference −290 −109 −126 % Difference −16.2% −15.6% −13.5% Dallas–Ft. Worth Forecast 5,030 1,897 2,918 Actual 4,756 1,779 3,046 Difference 274 118 −128 % Difference 5.8% 6.6% −4.2% Note: Atlanta -- Atlanta Regional Commission; Chicago -- Chicago Area Transportation Study; San Francisco -- Metropolitan Transportation Commission; Washington, D.C. -- Metropolitan Washington Council of Governments; Portland -- Metro Portland; Dallas–Ft.
|
From page 79... ...
Future Data Challenges The challenges of obtaining appropriate and sufficient data for modeling are magnified by such emerging issues as changes in lifestyle that affect the traditional methods used to conduct home interview surveys, changes in census products, and the need for data on daytime populations. Collection of Travel Data While MPOs today have data processing capabilities far superior to those applied in the original urban transportation studies, technological developments and other considerations have combined to make the methodology of home interview surveys more problematic.
|
From page 80... ...
. Data on Daytime Populations Travel models are used for typical travel behaviors but are increasingly being used as well for planning of evacuations and relief efforts due to natural disas ters, immunization programs, and risk assessments for homeland security.
|
From page 81... ...
BIASES ARISING FROM THE INSTITUTIONAL CLIMATE Forecasts of costs, traffic, and revenue are made for the purpose of assessing courses of action. They are used regularly in planning and designing transportation facilities and policies.
|
From page 82... ...
. They found that costs are far more likely to be 100 <80% of forecast ridership 80 80% or more of forecast ridership Percent of Projects 60 40 20 0 1990 2004 Year of Study FIGURE 5-2 New start rail transit forecasts and actual ridership, 1990 and 2004.
|
From page 83... ...
Of interest, the magnitude of forecast errors has not been declining over time. This suggests that, with some exceptions such as FTA New Starts, the performance of travel demand models and transportation cost estimates is not improving despite the efforts of many transportation researchers to improve the techniques employed.
|
From page 84... ...
biases arising from the institutional climate in which the models are used. Inherent Weaknesses of the Models Critiques of the ability of the current modeling process to address the issues with which MPOs must deal are numerous.
|
From page 85... ...
The conventional travel demand models make use of networks, both highway and transit, in which impedances are averages over an extended period, reflect no uncertainty or unreliability, and are not representative of the conditions that would be expected or found by an individual traveler at the time a trip choice is made. The issues that the current widely used metropolitan travel demand forecasting process cannot adequately characterize as a consequence of these deficiencies include the following: • Road pricing, including high-occupancy travel lanes; • Time-specific policies, such as parking, work schedules, or scheduling of truck deliveries; • Hourly speeds or traffic volumes; • Improvements to traffic operations; • Nonmotorized travel; • Peak spreading and highly congested networks; and • Goods movement.
|
From page 86... ...
MPOs, together with the federal government and the states, should determine data requirements for validating current travel forecasting models, meeting regulatory requirements, and developing freight models and advanced travel models. Biases Arising from the Institutional Climate Forecasts are always subject to error and uncertainty, but they should be pre pared honestly, data should not be falsified, and assumptions should be cho sen on defensible and technical grounds and not because they favor certain outcomes over others.
|
From page 87... ...
Therefore, steps must be taken to improve both current and future practice in metropolitan travel forecasting. Conclusion The focus of this chapter has been on the shortcomings of current travel forecasting models for their intended uses.
|
From page 88... ...
1990. Urban Rail Transit Projects: Forecast Versus Actual Ridership and Costs: Final Report.
|
From page 89... ...
In Expert Forum on Road Pricing and Travel Demand Forecasting, Proceedings, Office of the Secretary, U.S. Department of Transportation, Washington, D.C.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.