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U S I N G A C T I V I T Y- B A S E D M O D E L S F O R P O L I C Y D E C I S I O N M A K I N G 179
ADDRESSING POLICY ANALYSIS NEEDS ments using the proposed activity-based modeling
approach. First, many variables in an aggregate, trip-
The following discussion summarizes some specifics of based model must be introduced through the use of seg-
how the proposed modeling approach would address mentation, which significantly limits the number of
some of the specific policy analysis needs described above. variables that can be included in the model. Adding fur-
ther segmentation to a typical cross-classification trip
production model (likely with only two or three dimen-
Pricing Analysis sions) to account for different trip-making characteris-
tics in denser, transit-oriented areas would require the
The traffic forecasting procedures for toll facilities and household survey data to be segmented by additional
managed lanes have been a topic of considerable discus- dimensions, often beyond the ability to obtain statisti-
sion recently. Various aspects of existing procedures have cally significant estimates of trip rates given the limita-
been criticized, including the assumed values of time for tions of the existing sample. The activity-based modeling
various market segments of travelers, the aggregate approach, where individual daily activity patterns are
nature of the process (which requires fixed values of time simulated, permits description of individuals using a
for each segment), the difficulty in modeling time of day much richer set of variables.
outside a tour-based approach, and the static nature of Planning judgment and travel behavior data also sup-
the traffic assignment process, which ignores the effects port the expectation that having a variety of attractions
of the buildup and dissipation of queues. located in close proximity in the urban centers, including
Activity-based approaches present some advantages workplaces, other businesses, and shopping and enter-
over conventional modeling procedures in addressing tainment opportunities, would have an effect on trip
some of these issues. One major advantage is that mod- chaining, as individuals might choose to combine activi-
eling individuals in the synthetic population provides an ties that can be accomplished in the same vicinity. Obvi-
opportunity to use distributed values of time rather than ously, a tour-based approach is required to capture the
fixed values for a relatively small number of market seg- effects of trip chaining.
ments. For example, say that it would take a value of Finally, data also suggest that persons living or work-
time of $12/h for a certain geographic market to find ing in higher-density transit-oriented areas should have
using a particular toll road segment desirable. If the aver- greater opportunities to use transit and nonmotorized
age value of time for the market segment were $10/h, modes. However, properly reflecting these opportunities
then the model would estimate that no one from that in the model requires a combination of capabilities: mod-
segment would use the toll road. However, if a value of eling travel in tours so that, for example, secondary tour
time distribution were used with an average value of trips, stops, and modes can be shown to be compatible
$10/h but with a 20% probability of having a value of with transit as the primary mode of the tour (as they will
time of greater than $12/h, there would be demand esti- sometimes be within walking distance); destination
mated for the toll road within this market segment. choice models that can operate at sufficient geographic
Another major advantage is that demand for road- detail so as to locate some secondary stops within the
ways where tolls vary by time of day can be modeled transit-oriented development; and fine geographic detail
much more accurately. Time-of-day decisions for activi- on stop locations so that walk distances can be accu-
ties must consider not only the time when the trip to or rately calculated (so that walk choices in the mode choice
from the activity takes place, but also the trip in the other models are accurately estimated).
direction and the duration of the activity itself. For
example, if someone wishes to consider shifting his
departure time for a work trip to avoid a high-peak- Transportation Project Analysis
period toll, he or she would likely also need to consider
the amount of time needed to be spent at work and The use of disaggregate microsimulation of individuals
whether the time shift for the trip to work might shift the provides some advantages to the analysis of new trans-
departure time from work to or from a peak period with portation projects, particularly the extensive transit
a high toll. Obviously a model that treats individual trips investments planned for the Denver area. One of the key
independently cannot include such considerations. questions involved in the analysis of transit investments
involves the identification of how specific groups of the
population (for example, persons from low-income
Urban Centers and Transit-Oriented Development households) benefit from the investments. In conven-
tional models, demographic market segmentation is not
There are several advantages to modeling travel by resi- carried through beyond the mode choice step, so some
dents, workers, and visitors in these types of develop- model results cannot be differentiated by market seg-
