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Conversion Model, can be input. By explicitly including · Boston Logan International Airport (BOS),
variables for off-airport parking prices, the model also · Chicago O'Hare International Airport (ORD),
allows the user to examine the composite effects of alterna- · Huntsville International Airport (HSV),
tive pricing scenarios, such as main garage pricing changes · McCarran International Airport (LAS),
that are mirrored by off-airport lot pricing reactions, or · Miami International Airport (MIA),
main garage pricing changes alone. (20) · Oakland International Airport (OAK),
· Port Columbus International Airport (CMH),
· Portland International Airport (PDX),
ACRP Project 10-06 Airport Parking · San Antonio International Airport (SAT),
Forecast Model · San Diego International Airport (SAN),
A model for testing resident airline passenger mode-share · Seattle-Tacoma International Airport (SEA),
behavior was developed for ACRP Project 10-06 to provide · Tampa International Airport (TPA),
analysts with a tool for predicting, at a high level, likely out- · Tulsa International Airport (TUL), and
comes of strategies being considered to address constrained · Washington Dulles International Airport (IAD).
airport parking. The model, referred to as the General Airport
Parking Forecast Model, was developed based on data col- To provide reliable results for the airport-specific model,
lected at 14 U.S. airports. An airport-specific version of the the sample size of the data collected at PDX was larger than the
model was also developed based on data collected at PDX, sample sizes collected at the other 13 airports for the General
which was among the 14 airports used for data collection. Airport Parking Forecast Model. The PDX sample was weighted
These two versions of the model were developed to provide for inclusion in the general airport model so it would not skew
airport operators and others with information regarding the the results of the general model.
benefits and tradeoffs of developing their own airport-specific The models were developed in Microsoft Excel and offer
models versus using the general airport model. The research user-friendly interfaces. They are multinomial logit models
team evaluated the effectiveness of the models by comparing based on data collected in an online stated preference survey
projected results of identical policy scenarios for PDX from of airline passengers at each of the sample airports, conducted
the airport-specific model and the general airport model, and between April 21, 2009 and May 4, 2009. Stated preference
found both to be effective for estimating the results of policy survey data are useful in estimating causeeffect relationships
scenarios, as described in the rest of this section. for airport access. A stated preference survey is designed to
The general airport model was developed as a tool for any collect much of the information obtained in an O&D survey
commercial airport operator to use to estimate results at its that is necessary to understand the respondent's ground access
airport without undergoing an extensive data collection effort. behavior on a previous trip (referred to as "revealed prefer-
The model can be used to compare results between scenarios ence" data), including mode, trip purpose, trip origin, travel
for a specific airport. It calculates the results using the under- party size, length of stay, and other relevant information, as
lying survey data from the 14 U.S. airports and the character- well as data on future ground access choices airline passengers
istics of the available modes and resident airline passenger would make under different policy scenarios, referred to
mode shares for the specific airport that would be added to as "stated preference" experiments. Stated preference experi-
the inputs page by the analyst. The general airport model and ments were used to test the effects on airport choice and
instructions on how to use it are available on the CD-ROM parking behavior of a wide range of variables that are likely
that accompanies this report. to influence decisions on whether or not to use airport parking,
In comparison to the general airport model, an airport- including location, price, availability, shuttle service quality
specific model will produce estimated results with a higher level and availability, and availability and level of service of alterna-
of accuracy for the airport, may include more mode options tive HOV options to access the airport. An example of a stated
that are specific to the airport, and can be structured to test preference experiment from the survey is shown in Figure 2.
more strategies and strategies that are more relevant to the The methodology used for collecting the stated preference sur-
specific airport environment. Such a model requires an invest- vey data, as well as the survey instrument, are provided in the
ment of time and money by the airport operator, including the Final Report for ACRP Project 10-06.
collection of survey information for model development. A discussion of both the general airport and airport-specific
The airports included in this research have experienced parking forecast models is provided in the following sections.
constrained parking conditions within the past 10 years. The The level of reliability and results of the general airport model
airport-specific model is based on data collected at PDX. The also are discussed. To achieve more detailed results, airport
general airport model is based on data collected at the follow- operators may consider developing a model specific to their
ing airports: airport conditions and characteristics, so a comparison of the
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Source: Resource Systems Group, Inc., 2009.
Figure 2. Example of a stated preference experiment from ACRP Project 10-06
Stated Preference Survey.
two models and a discussion of approaches for estimating the ity, and a drop-off fee for private automobiles transporting
effects of strategy implementation from the model results also passengers in the pickup and drop-off mode. The model does
are provided. not allow the user to test the relationship between the use of
parking owned by the airport operator and privately operated
parking. Privately operated parking is included as part of the
General Airport Parking Forecast Model
mode category for park and ride shuttle to terminal. The model
The General Airport Parking Forecast Model captures the also does not have the capability to account for the severity
difference between large-hub airports and small- or medium- of the parking constraint at an airport. The Final Report for
hub airports and can be used to test strategies at any small-, ACRP Project 10-06 provides recommendations for future
medium-, or large-hub airport. The model provides planning- enhancements to the model to address these limitations.
level insight into potential airport operator and other trans- The research team used industry standard modeling meth-
portation agency policies to address constrained parking. As ods to determine model segments and coefficients that best fit
such, it is a useful tool for airport policymakers to use in eval- the stated preference data set. During model estimation, it was
uating a range of potential strategies being considered by observed that behavioral differences existed between business
reviewing the relative changes in mode shares for each strat- and nonbusiness trips that could be captured by using separate
egy tested. choice models. The two separate choice models were incorpo-
Examples of strategies that may be tested with the model rated into the General Airport Parking Forecast Model. From
include changes in parking rates, changes in the level of service this, the Excel-based forecast model was created by calculating
of remote parking shuttles, changes in the level of service or the probability of using an access mode for a specific scenario
fares for HOV modes, the introduction of transit at airports and by applying the probability to the sample to calculate
that do not offer transit, the addition of remote parking capac- respondent-level preferences for each access mode.
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Using the General Airport Parking Forecast Model. The ing, uniform percentage increases to each, increases in
general airport model, created in Microsoft Excel 2007, is avail- only one category, or changes that examine the relationship
able on the CD-ROM that accompanies this report. Model between pricing in each category);
inputs include base case resident airline passenger mode-share · Improvements or reductions in shuttle service between the
distribution data for resident airline passengers traveling for terminal and remote parking facilities, which include the
business and nonbusiness purposes, and travel times and rates frequency to the terminal or wait times;
for parking and other modes, as shown in Table 7. The travel · Improvement or degradation in the travel times of other
time pricing inputs are also shown in Table 8. The most accu- modes in relation to automobile travel time; and
rate source for resident airline passenger mode-share data is a · Changes in passenger fares for modes that are alternatives
survey of O&D airline passengers, as described in Chapter 8. to driving and parking, including instituting a drop-off fee
Step-by-step instructions for testing strategies for alleviat- for automobiles transporting airline passengers for pickup
ing constrained public parking in the general airport model and drop-off at the curbside.
are as follows:
Three example policy scenarios were tested in the general
1. Enter base case mode share for resident business and res- airport model. The example policy scenarios, along with an
ident nonbusiness passengers into base case ground access interpretation of the model results, include the following:
mode shares cells. If the mode shares for resident business
· General Airport Model Scenario No. 1: Doubling of Park-
and resident nonbusiness passengers are unknown, the
ing Fees--One of the key strategies an airport operator will
mode share for resident airline passengers can be entered
consider to try to influence parking mode share is to change
into both sets of cells. As noted previously, the model does
parking rates. In the scenario shown in Table 10, a dou-
not distinguish between privately operated off-airport park-
bling of the parking fees at a hypothetical small-hub airport
ing and remote public parking. Both categories are included
is tested. Although airport operators do not frequently dou-
in "park and ride shuttle to terminal."
ble the fees for public parking, the example illustrates how
2. Enter the proportion of business and nonbusiness resident
a dramatic change in parking fees would affect travel behav-
airline passengers in the base case column. ior. For purposes of this example, doubling parking fees is
3. Enter actual or estimated base data for pricing and travel representative of constraining parking because this dramatic
times into the base case column. increase in parking fees is likely to influence passenger per-
4. Enter pricing and travel times appropriate for the strategy spective of the availability of parking. In this scenario, 16%
being considered. of total airline passengers accessing the airport (account-
5. Click the cursor on "calibrate to base case" button. Instruc- ing for 40% of the passengers that would have parked for
tions for how to set macro permissions in Excel for optimum the duration of their trips) shifted primarily to the drop-
use of the model are included in model documentation. off mode (11%), followed by the taxicab mode (2%). This
6. The mode-share distribution will be shown in the model analysis illustrates the relationship between parking con-
output section of the user interface page. Table 9 presents straints and shifts to drop-off modes.
an example of results from the model output tables. · General Airport Model Scenario No. 2: Reduction of
Parking Fees--A second scenario was tested to measure
Application of the General Airport Model. The Gen- the influence that a 50% reduction of parking fees would
eral Airport Parking Forecast Model can be used to compare have on passenger ground access behavior at a large-hub
the relative effects of many different strategies being con- airport. This scenario, shown in Table 11, is presented to
sidered. Strategies may be tested individually or together. To demonstrate the relationship between changes in perceived
understand the effect of each strategy, the strategies should parking constraints (or, in this case, reduced constraints)
be evaluated individually before considering the adoption and ground access mode-share distribution. In this sce-
and implementation of a combination of strategies. Common nario, the airport has a significant transit mode-share of
examples of strategies an airport operator may consider include 15%; however, this mode share was minimally affected by
the following: the policy to influence passenger parking behavior. The
shift in mode share occurred from drop-off modes (private
· Parking rate changes at different parking facilities (the automobile and taxicab) to the use of parking facilities.
model allows the user to test parking rate changes for the · General Airport Model Scenario No. 3: Addition of
parking supply within walking distance of the terminal and Parking--The presence of off-airport parking has a mean-
the remote parking supply, but does not distinguish park- ingful effect on an airport's ground access mode-share dis-
ing beyond these two categories; rate changes may include tribution. Although the stated preference survey did not
absolute dollar increases for terminal area and remote park- distinguish between on-airport parking that required a
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Table 7. Model inputs for the General Airport Parking Forecast Model.
Airport Specific Base Case & Policy Scenario Levels Base Case Policy Scenario Units
Park & Walk to Terminal Parking Fee $25.00 $35.00 per day
Park & Ride Parking Shuttle to Terminal Parking Fee $18.00 $20.00 per day
Parking Shuttle Riding Time to Terminal 10 10 minute s
Wait Time for Shuttle 10 5 minute s
Airport Drop Off Charge N/A $0.00 $/t rip
Taxi/Limo/Towncar Fare by Distance $2.0 0 $2.50 $/mi le
Transit Fare $3.0 0 $3.50 $/t rip
Shared Van Fare by Distance $1.7 5 $2.00 $/mi le
Scheduled Bus Fare by Distance $0.2 0 $0.20 $/mi le
Additional Transit Time (over auto travel time) 0.30 0.30 mins/m ile
Additional Shared Van Time (over auto travel time) 0.30 0.30 mins/m ile
Additional Bus Time (over auto travel time) 0.30 0.30 mins/m ile
Amount of Remote Parking 1.00 1.20 (1,000s of spac es)
Alternative Availability Base Case Policy Scenario
Park & Walk to Terminal TRUE TRUE
Park & Ride Shuttle to Terminal TRUE TRUE
Taxi/Limo/Towncar to Terminal TRUE TRUE
Dropped Off at Terminal TRUE TRUE
Transit to Airport TRUE TRUE
Shared Van to Airport TRUE TRUE
Scheduled Bus to Airport TRUE TRUE
Resident Air Passengers Trip Purpose Base Case
Business Trips 29%
Non-Business Trips 71%
Airport Size Small/Medium Hub
Base Case Ground Access Mode Shares Business Trips
Park & Walk to Terminal 32%
Park & Ride Shuttle to Terminal 17%
Taxi/Limo/Towncar to Terminal 17%
Dropped Off at Terminal 14%
Transit to Airport 10%
Shared Van to Airport 9%
Scheduled Bus to Airport 1%
Total 100%
Base Case Ground Access Mode Shares Nonbusiness Trips
Park & Walk to Terminal 13%
Park & Ride Shuttle to Terminal 18%
Taxi/Limo/Towncar to Terminal 9%
Dropped Off at Terminal 32%
Transit to Airport 18%
Shared Van to Airport 7%
Scheduled Bus to Airport 3%
Total 100%
Source: Resource Systems Group, Inc., November 2009.
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Table 8. Pricing and travel time model inputs,
General Airport Parking Forecast Model (base case).
Model Input Units
Park and Walk to Terminal Parking Fee Per day
Park and Ride Shuttle to Terminal Parking Fee Per day
Shuttle Riding Time to Terminal Minutes
Wait Time for Shuttle Minutes
Airport Drop-Off Charge1 $ per trip
Taxi Fare by Distance $ per mile
Transit Fare $ per trip
Van Fare by Distance $ per mile
Scheduled Bus Fare by Distance $ per mile
Additional Transit Time (over automobile travel time) Minutes per mile
Additional Van Time (over automobile travel time) Minutes per mile
Additional Bus Time (over automobile travel time) Minutes per mile
Amount of Off-Airport Parking Spaces (in thousands)
Note:
1
The drop-off fee is a per trip fee charged to all passengers dropped off by private
automobile at the terminal.
Source: Resource Systems Group, Inc., August 2009.
Table 9. Example of output from the General Airport Parking Forecast Model.
Business Trips
Resident Access Mode Share Base Case Policy Scenario Absolute Difference % Difference
Park & Walk to Terminal 32% 23% -9% -30%
Park & Ride Shuttle to Terminal 17% 23% 6% 35%
Taxi/Limo/Towncar to Terminal 17% 14% -3% -17%
Dropped Off at Terminal 14% 19% 5% 35%
Transit to Airport 10% 11% 1% 14%
Shared Van to Airport 9% 9% 0% -1%
Scheduled Bus to Airport 1% 1% 0% 38%
Total 100% 100%
Nonbusiness Trips
Resident Access Mode Share Base Case Policy Scenario Absolute Difference % Difference
Park & Walk to Terminal 13% 9% -4% -35%
Park & Ride Shuttle to Terminal 18% 19% 1% 5%
Taxi/Limo/Towncar to Terminal 9% 7% -2% -21%
Dropped Off at Terminal 32% 37% 5% 15%
Transit to Airport 18% 19% 1% 4%
Shared Van to Airport 7% 7% 0% -7%
Scheduled Bus to Airport 3% 4% 1% 17%
Total 100% 100%
All Trips
Resident Access Mode Share Base Case Policy Scenario Absolute Difference % Difference
Park & Walk to Terminal 19% 13% -6% -32%
Park & Ride Shuttle to Terminal 18% 20% 2% 13%
Taxi/Limo/Towncar to Terminal 11% 9% -2% -20%
Dropped Off at Terminal 27% 32% 5% 18%
Transit to Airport 16% 17% 1% 6%
Shared Van to Airport 8% 7% 0% -5%
Scheduled Bus to Airport 2% 3% 0% 19%
Total 100% 100%
Source: Resource Systems Group, Inc. 2009.
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Table 10. Doubling of parking fees at a small-hub airport.
All Trips
1
Access Mode Share Base Case Policy Scenario Absolute Difference Percent Difference2
Park and Walk to Terminal 15% 6% -9% -57%
Park and Ride Shuttle to Terminal 25% 18% -7% -27%
Taxicab to Terminal 10% 12% +2% +22%
Dropped Off at Terminal 40% 51% +11% +27%
Transit to Airport 1% 1% 0% +21%
Shared Van to Airport 4% 5% +1% +22%
Scheduled Bus to Airport 5% 6% +1% +27%
Total3 100% 100%
Notes:
1
Although this scenario is representative of conditions at a small-hub airport, which is less likely to be well served by public transit
compared to large-hub airports, the stated preference survey experiments did include public transit options.
2
Percent difference calculations may differ due to rounding.
3
Totals may not add to 100% due to rounding.
shuttle bus to access the terminal and privately operated the airport and in the terminal area will decrease because,
off-airport parking, a scenario was tested in the constrained for every one-way airline passenger trip, passengers who
parking forecast model in which 5,000 remote spaces (cor- are dropped off generate two vehicle trips and passengers
related to the "park and ride shuttle to terminal" mode) were who park for the duration of their trips only generate one
added to the public parking supply. This scenario applies to vehicle trip. However, revenue implications to the airport
the addition of 5,000 spaces to either the on-airport public operator also would need to be considered.
remote parking supply or the off-airport privately operated
parking supply. Table 12 presents the results of this sce- As demonstrated in the example scenarios, the General
nario. The addition of remote parking shifts mode share Airport Parking Forecast Model can be used to test a variety
mainly from the "park and walk to terminal" and "dropped of changes (price and travel time) related to the provision of
of at terminal" modes to the "park and ride shuttle to termi- airport access modes that could be used to address constrained
nal" mode. This result implies that the addition of parking parking conditions. The estimates from this model represent
capacity does not generate significant demand for parking, averages from the 14 airports surveyed and airport-to-airport
as the overall share of passengers parking increased only two differences may not be fully represented when the model is
percentage points despite a significant increase in parking applied to a specific airport.
supply. In this circumstance, with the majority of the mode The General Airport Parking Forecast Model reasonably
shift coming from the "park and walk to terminal" mode represents the general magnitudes of changes in airline pas-
and the "dropped off at terminal" mode, vehicle trips to senger access mode choices, even for those airports that do not
Table 11. Reduction of parking fees by 50 percent at a large-hub airport.
All Trips
Access Mode Share Base Case Policy Scenario Absolute Difference Percent Difference1
Park and Walk to Terminal 5% 11% +6% +117%
Park and Ride Shuttle to Terminal 10% 15% +5% +48%
Taxicab to Terminal 30% 27% -3% -10%
Dropped Off at Terminal 30% 24% -6% -19%
Transit to Airport 15% 15% 0% -3%
Shared Van to Airport 5% 4% -1% -11%
Scheduled Bus to Airport 5% 4% -1% -19%
Total2 100% 100%
Notes:
1
Percent difference calculations may differ due to rounding.
2
Totals may not add to 100% due to rounding.
Source: Resource Systems Group, Inc., August 2009.
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Table 12. Addition of remote parking supply at a large-hub airport.
All Trips
Access Mode Share Base Case Policy Scenario Absolute Difference Percent Difference1
Park and Walk to Terminal 5% 4% -1% -25%
Park and Ride Shuttle to Terminal 10% 13% +3% 30%
Taxicab to Terminal 30% 30% 0% -2%
Dropped Off at Terminal 30% 29% -1% -3%
Transit to Airport 15% 15% 0% 0%
Shared Van to Airport 5% 5% 0% -2%
Scheduled Bus to Airport 5% 5% 0% -3%
Total2 100% 100%
Notes:
1
Percent difference calculations may differ due to rounding.
2
Totals may not add to 100% due to rounding.
Source: Resource Systems Group, Inc., August 2009.
have highly accurate access mode-share information available, strained airport parking, such as gross parking-derived rev-
and should prove useful as a planning-level model for any enues and the likely changes in the number of vehicle trips
airport with constrained parking. When the General Airport generated by airline passengers.
Parking Forecast Model is used and calibrated to the base An airport-specific parking forecast model was developed for
access mode shares for the airport under study, the results PDX as part of this research project. The model included access
should be interpreted as accurately representing relative modes, pricing, and time variables specific to PDX. As part of
changes when comparing pricing and other policies. For exam- the sampling plan, a larger number of responses was collected
ple, the differences in the mode-share distribution that results from the PDX catchment area than was collected in the sample
from a 10% increase in terminal parking prices compared to from each airport for the General Airport Parking Forecast
those that result from a 20% increase in terminal parking prices Model. This larger sample from a single airport allowed for the
should be accurately represented (e.g., within 15% or so, based development of a model specific to circumstances at PDX.
on variations in behavior among airports as observed in the PDX was selected because (1) the Port of Portland has dealt
models developed for this research project), as well as the dif- with policy-related constrained parking conditions since 2003,
ferences in mode-share distribution that result from the sce- (2) a light rail line to PDX opened in 2001, and (3) the public
narios presented in the example scenarios. However, the actual parking supply at PDX is supplemented by a privately operated
mode shares that result from pricing or policy changes may off-airport parking supply. In addition, the Port of Portland
differ from the model-estimated shares because of differences was one of two airport operators participating in this research
in behavior among airports that are not represented in the project that had the potential to field-test results and compare
general airport model. them to similar results from their own predictive tools.
An airport's specific characteristics could be represented in The model was developed using a similar methodology as
more detail and provide a higher level of predictive accuracy described for the General Airport Parking Forecast Model,
if an airport-specific survey and model were developed, as except that separate modules were not developed for business
described in the next section. and nonbusiness passengers.
The draft PDX parking model was field tested by a Port rep-
Airport-Specific Parking Forecast Model resentative to obtain feedback on the model with respect to its
ease of use and applicability of results. The model was received
An airport-specific parking forecast model is a customized favorably, except for a preference to segment the mode-share
model that represents the environment of a specific airport, distribution by business and nonbusiness travelers. It was
thereby increasing the model's overall utility. In comparison noted that the results for strategies tested were similar to the
to the General Airport Parking Forecast Model, a model devel- results from the PDX Air Passenger Demand Model.
oped specifically for one airport may include more mode
options that are specific to that airport and could be struc-
Value of Airport-Specific Parking Forecast Model
tured to test more strategies and strategies that are more rele-
vant to that specific airport environment. The airport-specific Development of an airport-specific parking forecast model
model may also include additional calculations of outcomes will most likely require new data collection and model devel-
related to strategies that have the potential to resolve con- opment by the airport operator or another interested party,
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which would take several months to complete and additional characteristics of PDX. Scenario No. 1 tested a 50% increase in
commitment and investment by the airport operator. Since this parking fees--from $30 to $45 for the "park and walk to termi-
is a specialized area, development of an airport-specific model nal" mode and from $8 to $12 for the "park and ride shuttle to
requires specialized expertise. The decision to commission a new terminal" mode. Scenario No. 2 tested implementation of a
airport-specific model versus using the General Airport Park- $10 drop-off fee at curbside. Tables 13 and 14 present the results
ing Forecast Model will be based on the need to obtain results from both the airport-specific model and the general airport
with a higher level of accuracy, with specificity to the airport, model. In reviewing these results, the differences should be con-
or with details not included in the General Airport Parking Fore- sidered rather than the mode-share distributions.
cast Model. The Final Report for ACRP Project 10-06 includes In the first scenario, the general airport model produces
recommendations for data collection and enhancements to the results that are similar to the PDX model. In the second sce-
model based on the research that the airport operator should nario, the share of customers dropped off at the terminal (the
consider when choosing between the General Airport Parking customers who would be affected by this policy change) differs
Forecast Model and development of an airport-specific model. by 4 percentage points, which could indicate that customers in
One measure of the usefulness of the airport-specific park- the 14-airport sample are generally less price sensitive than
ing forecast model is the assessment by the Port of Portland PDX customers or that they have fewer HOV options. More
representative that the model results were similar to the results policies would have to be tested to compare differences in
of the PDX Air Passenger Demand Model developed by the order to determine whether or not an airport operator should
Port of Portland in 2009. consider developing its own model or use the general airport
model to test policy scenarios.
Comparison of Airport-Specific
and General Airport Models Using Model Results to Estimate Impacts
of Strategy Implementation
A comparison of the results of the airport-specific parking
forecast model and the results of the General Airport Park- Potential enhancements to the general airport model that
ing Forecast Model provides some insight into the value of would increase its usefulness in estimating the effects of con-
developing an airport-specific parking forecast model. To strained airport parking include the addition of calculations of
evaluate the usefulness of the airport-specific model versus parking transaction parking revenue, vehicle trips generated by
the general airport model, the results from each model with airline passengers, and related changes to vehicle emissions.
identical policy scenarios applied to the PDX environment The mode-share input and output from the general airport
were compared. Both models were calibrated to the specific model can be used to estimate, at a high level, changes in vehi-
characteristics of PDX. cle trips and emissions by airline resident O&D passengers.
Two scenarios were developed to compare the results of the The methodology described in Chapter 8 under "Measuring
airport-specific and general airport models based on the specific Effects of Parking Strategies" (in subsections on vehicle traffic
Table 13. Comparison of general airport and airport-specific models
with 50-percent increase in parking fees.
Portland International Airport Mode Share
Policy Scenario
Representative General Airport Airport-Specific Policy Scenario
Access Mode Share Base Case Model Model Difference1
Park and Walk to Terminal 10% 5% 4% 1%
Park and Ride Shuttle to Terminal 15% 13% 12% 1%
Taxicab to Terminal 10% 11% 11% 0%
Dropped Off at Terminal 45% 50% 51% 1%
Transit to Airport 10% 10% 11% 1%
Shared Van to Airport 5% 5% 5% 0%
Scheduled Bus to Airport 5% 6% 6% 1%
Total 100% 100% 100%
Note:
1
Policy scenario difference calculations may differ due to rounding.
Source: Resource Systems Group, Inc., August 2009.
