Airport Ground Access Mode Choice Models (2008) / Chapter Skim
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Pages 105-141
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From page 105... ...
105 This appendix contains detailed technical summaries of selected airport ground access mode choice models discussed in the body of the report. The summaries document the technical details of the models, including the functional form adopted, market segmentation, causal variables included in the model, estimated parameter values, and goodness-of-fit measures where these have been reported in the literature or model documentation.
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From page 106... ...
motel courtesy vehicles, as well as conventional taxi use. This grouping of modes is likely to have a significant effect on the estimated model coefficients, because it implies that the modes grouped together for the purpose of model estimation have similar service characteristics.
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From page 107... ...
107 ASCs (termed model bias coefficients in the documentation) were then estimated to ensure that the model predicted the observed mode shares.
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drop-off alternative do not consider the operating cost of the vehicle for the return trip or assign any disutility to the time of the driver, this does not seem unreasonable, although in reality these effects are not likely to be constant across all air parties. Because the utility functions for the rental car alternative do not include any continuous variables (travel time or cost)
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From page 109... ...
109 occupancy for hotel/motel courtesy vehicles is likely to be greater than that for conventional taxi and limousine, owing to the sharedride nature of hotel/motel courtesy vehicles, resulting in an overestimate of vehicle trips for the taxi mode. However, the geographic pattern of this error is likely to be very uneven, because most hotel/motel courtesy vehicle trips are from areas fairly close to the airport, whereas taxi and limousine use is more widely distributed throughout the region.
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110 Travel Time Coefficients Travel Cost Coefficients Dummy Variable Coefficients Mode Const. Tree Coeff.
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From page 111... ...
111 Travel Time Coefficients Travel Cost Coefficients Dummy Coefficients Mode Const. IVTT OVTT Auto Acces s No.
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From page 112... ...
It makes no sense that given travelers will value their time at one amount when considering a high-priced mode and a different amount when considering a less expensive, but more time-consuming mode. Because the CTPS modelers were able to obtain a statistically significant difference in the model coefficients for different modes suggests that this is a result of specification problems with the models or problems with the model estimation data.
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From page 113... ...
113 period of analysis (e.g., average weekday or annual demand) using a survey expansion factor that relates the number of air passengers in the survey sample to the O&D passenger traffic at the airport for the period of analysis (accounting for forecast traffic growth for future years where necessary)
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From page 114... ...
The results of the stated preference survey were used to estimate a mode choice model that defined nine airport access modes, as follows: • Private vehicle parked at the airport for the duration of the air trip (drive and park) • Dropped off at airport by private vehicle (dropped off)
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From page 115... ...
115 for residents of the Chicago region and non-residents, although the available modes for these two market segments were different, as noted earlier. The estimated model coefficients for travel time and the dummy variables were constrained to be the same for O'Hare and Midway airports, whereas separate travel cost coefficients were estimated for each airport.
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From page 116... ...
These differences in the implied value of travel time across the market segments are troubling, because they directly affect the trade-off between travel times and cost, which is central to the evaluation of a new service that offers shorter travel times for a premium fare. Given the obvious importance of household income in explaining traveler behavior, both from the perspective of common sense and as demonstrated by the model estimation results, the classification of travelers into only two income categories must necessarily only provide a very approximate representation of the role of income in access mode choice.
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From page 117... ...
Coefficient Resident Business Resident Non-Business Non-Resident Business Non-Resident Non-Business Continuous Variables Total travel time (minutes) –0.092 –0.091 –0.092 –0.091 Travel cost -- low income ($)
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From page 118... ...
118 Param eter Resident Business Resident Non-Business Non-Resident Business Non-Resident Non-Business Modal Constants ($) O'Hare Airport Private vehicle parked for trip 34/ 95 36/81 N/A N/A Private vehicle dropped off –9/–24 –11/–23 –6/–17 4/9 Rental car N/A N/A 25/68 10/22 Taxi 17/46 17/37 40/110 32/71 Other private m ode 19/52 17/38 39/108 30/66 Airport Bus –42/–116 –25/–66 –42/–116 –25/–66 CTA train –4/–11 –11/–23 –4/–11 –11/–23 Other public m ode 24/66 8/17 34/93 22/48 Midway Airport Private vehicle parked for trip 25/33 22/59 N/A N/A Private vehicle dropped off –31/–41 1/2 2/2 1/3 Rental car N/A N/A 38/50 7/20 Taxi 7/9 14/37 64/83 23/61 Other private m ode 6/7 34/91 57/75 22/58 Airport Bus –79/–104 –35/–91 –79/–104 –35/–91 CTA train –2/–2 –1/–2 –2/–2 –1/–2 Other public m ode –25/–33 –23/–60 –28/–37 –29/–77 Notes: The two values shown for each coefficient are for low-income and high-income respondents, respectively.
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From page 119... ...
119 value of the coefficient for the intermediate station dummy variable would attempt to correct for this. Interpreting the implied values of the ASCs for the access modes to the Airport Express train requires some caution owing to the way that the associated costs and travel times were included in the stated preference experiments.
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From page 120... ...
Because the air passenger trip tables that were developed for the study did not include detailed air party characteristics, but only counts of passengers from each TAZ by market segment, the model application was based on average air party size and average air trip duration for each market segment in calculating travel costs, as well as the average percentage of rental cars that were not needed for other purposes than travel to and from the airport. Because logit choice models tend to exhibit strong nonlinearity with respect to the values of the explanatory variables, it is unclear what effect this might have on the results.
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From page 121... ...
121 to represent the number of originating average weekday passengers in 1991 and doubled to account for arriving passengers. These air passenger trips were then assigned to the much larger number of regional (TAZs)
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the air party was addressed in calculating travel costs, if at all. The cost assumptions appear to have been made on the basis of the travel cost for each air party.
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From page 123... ...
123 vary across the four market segments, reflecting difference in mode use across the segments. The implied value of in-vehicle time of $78/h appears reasonable for air passenger travel, particularly because it applies to both business and non-business travel.
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U.S. Federal Highway Administration and Florida Department of Transportation, Miami Intermodal Center Final Environmental Impact Statement, Report FHWA-FLA-EIS-95-01-F, Tallahassee, Fla., Dec.
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From page 125... ...
125 Rental car costs were calculated on the basis of $50 per day factored by the average trip duration and average air party size for each market segment. Apart from that this assigned the same cost to all air parties, irrespective of their actual trip duration, it also assumed that the full cost of renting the car was attributable to the airport access and egress trip.
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From page 126... ...
coefficient values estimated on data for one year cannot simply be applied to data for another year without adjustment for changes in real income levels (and hence the perceived value of time) between the two years.
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From page 127... ...
127 Model Fit The model documentation did not provide any information on the statistical significance of the estimated values of the model coefficients or the overall fit of the model to the estimation data. Model Application The mode choice model was used to estimate transit ridership for two future years, 2005 and 2020, and three project alternatives: a continuation of the AirBART shuttle (no-project alternative)
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From page 128... ...
Private vehicle -- drop off 36% Private vehicle -- parked 24% Rental car 19% Taxi 4% Limousine 2% Shared-ride van 4% Light rail transit 6% Hotel shuttle 4% Charter/tour bus 1% Market Segmentation Residents -- Business trips Residents -- Non-business trips Non-residents -- Business trips Non-residents -- Non-business trips Explanatory Variables Travel time (in-vehicle time, wait, onairport time) Travel cost/ln(household income)
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129 Coefficient Model 1 Model 2 Variables Drop off cost ($) –0.0195 –0.0195 Travel time (minutes)
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From page 130... ...
not clear why the RAZ bus was included as an option for external trips at all or why the hotel shuttle was considered as an option for resident trips. There are a number of counterintuitive or surprising values for the ASCs.
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From page 131... ...
131 Model Fit The initial Cambridge Systematics model estimation results include t-statistics for the coefficients for each variable and measures of overall goodness-of-fit of the model, including the final value of the log likelihood and the improvement over the log likelihood with zero coefficients or constants only. The overall improvement in the goodness-of-fit of the model from the inclusion of the continuous variables is not particularly large.
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From page 132... ...
factor was included in the private vehicle utility function for visitor trips to account for the inconvenience for drivers dropping off air passengers (the details of this factor are not given in the report)
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From page 133... ...
133 them to the airport and therefore either rent a car to meet their local transportation needs or use public modes. To explain these choices in a situation when the model has assumed that being dropped off by private vehicle is an option that is available, the values of the ASCs have to be increased.
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From page 134... ...
the Santa Clara countywide travel demand model. Although these have similar values for travel time components (and walking distance)
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135 ration (termed drive & park) , drop off by private vehicle (termed driven in car)
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From page 136... ...
explicitly included in the model. Business travelers will tend to have higher incomes on average than non-business travelers.
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From page 137... ...
137 might varying between about 7% and 14%, with a central estimate of 9.3%. The forecasts of ridership applying the mode choice model to the base case service scenario gave a mode share of 9.3% for 2001 traffic levels, rising to 9.7% for 2021 traffic levels.
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From page 138... ...
0.53079 0.14119 0.28186 0.20884 0.13157 0.07445 0.23525 0.09404 0.10991 0.23545 0.41689 0.13338 0.18127 0.40598 Rail Routes Coach Taxi Kiss & Fly Park & Fly Rail Routes Rail Routes Coach Coach Taxi Taxi Kiss & Fly Kiss & Fly Park & Fly Park & Fly Rail Routes Coach Taxi Kiss & Fly Park & Fly Segment 1 -- U.K. Business Domestic Mode Choice Structure Segment 3 -- U.K.
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From page 140... ...
generalized cost for the mode by the square root of the direct driving distance to the airport. There are no calibration parameters as such, although different values of time are assumed for each market segment and different weights are applied to waiting time for some market segments.
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From page 141... ...
141 Model Coefficients The values for the various model parameters that were used in the SERAS study are shown in Table D28. Air passenger value of time and vehicle operating costs are given in 1998 pence.
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