Airport Ground Access Mode Choice Models (2008) / Chapter Skim
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The prediction of air passenger and airport employee mode choice decisions for travel to and from the airport forms a key analytical component of airport landside planning, as well as airport system planning. However, there is currently no generally accepted and validated approach to modeling how airport users will change their access or egress mode in response to changes in the airport ground transportation system.
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car use by non-residents of a region and how best to account for the role of traveler income in the mode choice process. In addition, there has been almost no attention given to how reliably existing models predict air passenger access mode use when circumstances change from those from which the model was developed.
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model coefficients that best explain the observed values of the variable that the model is intended to predict, termed the dependent variable, using the observed values of the explanatory variables, termed the independent variables. The extent to which the model is able to reproduce the observed values of the dependent variable for any given set of values of the independent variables is referred to as the goodness-of-fit of the model and is an important measure of its usefulness.
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The overall process of developing an airport access mode choice model is summarized in Figure 1 and discussed in more detail in chapter two of this report. The basic concept underlying most disaggregate discrete choice analysis is that each alternative in the choice set provides the decision maker with some utility that can be expressed in terms of measurable or observable characteristics of both the decision maker and the alternative (e.g., the travel time involved or the income level of the decision maker)
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grouping similar modes or sub-modes into separate groups or nests in a choice structure referred to as a NL model, as illustrated by Figure 4 in chapter three. This figure (from a ridership study for a proposed airport express train in Chicago)
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forecasting study for a proposed airport express train serving the two Chicago airports, a travel demand forecast study for the planned Miami Intermodal Center, a ridership analysis of a planned automated people mover connection between Oakland International Airport and the nearby Coliseum station of the Bay Area Rapid Transit system, and a revenue and ridership forecasting study for a proposed Air Rail Link between Toronto Union Station and Lester B Pearson International Airport.
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The modes available for resident and non-resident trips will generally be different because non-residents do not have the option of parking a private vehicle at the airport (indeed this would make no sense because their visit to the region begins at the airport and they return to the airport at the end of their stay)
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models for home-based work trips and then estimating alternative specific constants to calibrate the model predictions to survey data on airport employee travel. The most common way to model employee travel to and from airports is to treat the airport in exactly the same way as any other transportation analysis zone in the regional travel demand model and use the trip generation, trip distribution, and mode choice sub-models for home-based work trips to generate the number of person and vehicle trips associated with airport employee travel.
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From page 9... ...
the concerns about the reliability of even applying them to different situations at the airports for which they were developed. • Airport Ground Access Models in the Regional Planning Process Although modeling airport access mode choice by air passengers and, to a lesser extent, airport employees, has largely been restricted to specialized studies addressing airport landside and system planning issues, there is a growing interest in explicitly modeling such trips in the regional transportation planning process.
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From page 10... ...
• Conclusions and Further Research Airport ground access and egress mode choice models play a critical role in airport landside planning studies and modeling traffic on the regional transportation system in the vicinity of airports. The ability to predict how air passenger and airport employee access and egress mode use will change in response to changes in the airport landside access system or other anticipated changes in the regional transportation system is essential to the proper evaluation of proposed measures and projects.
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