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Innovations in Travel Demand Modeling, Volume 2: Papers (2008)

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Suggested Citation:"T57054 txt_158.pdf." National Academies of Sciences, Engineering, and Medicine. 2008. Innovations in Travel Demand Modeling, Volume 2: Papers. Washington, DC: The National Academies Press. doi: 10.17226/13678.
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There are no easy answers. If MPOs are motivated to transition to the new wave of model systems only if activity- based models perform better than four- step travel models, then the more important question is: What constitutes a better model? If a better model is defined in terms of meeting a higher standard of valida- tion with the same number of or fewer adjustments to model components and parameters, then it is likely that the answer to both questions is yes. Clearly, this is open to debate. The debate also speaks to the merit of performing comparisons with four- step models. There is no doubt that any model can be adjusted, refined, tweaked, and— if all else fails— hammered to replicate base- year condi- tions. Thus, simply comparing models is not enough. This, the authors believe, is important because the state of the practice appears to be focused on using replication of base- year travel patterns as the sole or primary yard- stick to assess models’ performance. On the other hand, the primary objective of travel model development is forecasting future travel patterns when conditions may be quite different from base- year conditions or assessing travel pattern shifts after the implementation of a major change in transportation services or policies, not repli- cating base- year patterns. Thus, the emphasis needs to be on capturing travel behavior patterns adequately from base- year data, so that these behavioral patterns are transferable. The above discussion raises the issue of assessing the performance, usefulness, and robustness of alternative travel demand modeling, without focusing on replicating base- year travel patterns. This issue is discussed next. ASSESSMENT OF ACTIVITY- BASED TRAVEL DEMAND MODELS The question of what constitutes a better model is open to debate. There is a belief that the superiority of a model is best judged in terms of the validation to base- year traf- fic conditions. However, given that any model can be adjusted to replicate a given set of base- year traffic con- ditions, such measures are not always useful. The quality of a travel demand model system is better judged on its ability to respond to a range of scenarios and policies of interest. It is in this context that a true assess- ment can be performed and comparisons between existing four- step travel models and newer activity- based model systems become meaningful. Thus, assuming that there are two models— an existing four- step travel model and a newer activity- based travel model— that have been vali- dated to a set of base- year traffic measures, here is how the performance, usefulness, applicability, and robustness of the model systems can be assessed and compared. Changes in Land Use, Socioeconomic, and Demographic Characteristics Travel demand models should be responsive to changes in land use, socioeconomic, and demographic character- istics (i.e., the inputs that play a key role in driving travel forecasts). Activity- based model systems should be sub- jected to sensitivity tests in which population and employment characteristics are altered, both across the region and in selected zones, land use subdivisions, or market areas. Characteristics that might be subjected to change include population and employment totals; household distributions by zone, income, car ownership, size, dwelling unit type, and number of children; employ- ment distributions by zone and occupation, industry, and type; and person distributions by age, employment sta- tus, and gender. These variables should be subjected to a range of changes. Changes in Multimodal Transport Network Characteristics Travel demand models should be responsive to changes in transport network characteristics, which directly impact modal level of service attributes such as distance, time, and cost. There are a variety of ways in which these changes can be introduced. First, attributes associated with existing modal facilities may be changed. Attributes such as highway network speeds and transit route fre- quencies may be altered. Second, new facilities may be introduced. New highway links, new transit routes, new transit stops, new bicycle and pedestrian facilities, and so on may be introduced into the system. A consideration in determining the efficacy of a model is to examine the model’s ability to quantify induced or suppressed travel demand that may occur because of the modal change. Implementation of Transportation Policies Travel demand models should be responsive to a range of contemporary and emerging transportation policies and issues. These include, but are not necessarily limited to, • Pricing policies such as value pricing, variable (time of day) pricing, area- based congestion pricing, parking pricing, tolls, public transit fare policies (free fare zones, free intermodal transfers, and so forth), cash subsidies, fuel prices and taxes, and employer reimbursement schemes; • Policies aimed at encouraging alternate mode use including HOV–HOT lanes, rideshare programs, mixed land use development, transit- and pedestrian- oriented 158 INNOVATIONS IN TRAVEL DEMAND MODELING, VOLUME 2

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TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 2: Papers includes the papers that were presented at a May 21-23, 2006, conference that examined advances in travel demand modeling, explored the opportunities and the challenges associated with the implementation of advanced travel models, and reviewed the skills and training necessary to apply new modeling techniques. TRB Conference Proceedings 42, Innovations in Travel Demand Modeling, Volume 1: Session Summaries is available online.

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