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Airport ground access and egress mode choice models play a critical role in airport landside planning studies and model- ing traffic on the regional transportation system in the vicin- ity 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 sys- tem is essential to the proper evaluation of proposed mea- sures and projects. However, these decisions are influenced by very different factors from those affecting general re- gional travel patterns and the range of transportation options available to airport travelers are often quite different from those for other types of regional trips. Therefore, there is a need for specialized models that can represent these mode choice decisions as well as the means to integrate these mod- els or their output into the regional traveling modeling process. Aside from the need to predict ground access mode use at a given airport, air passenger ground access mode choice also affects airport choice in regions served by multiple commer- cial airports. The relative accessibility of each airport is one of the key determinants in air passenger choice of airport (to- gether with the air service offered at each airport) and for any given traveler the accessibility of an airport is influenced not only by the driving time needed to reach it, but also by the alternative ground transportation options that are available. In those cases where regional planners or local airport authorities wish to encourage the use of secondary airports serving the region, or to explore the feasibility of construct- ing a new airport, improvements to the ground access system may be one way to influence air passenger choice of airports and in turn the willingness of airlines to provide or expand air service at those airports. As a result, the development of air passenger ground access mode choice models has been the subject of ongoing research for more than 30 years. Over this period, the state of practice has slowly evolved from relatively simple multino- mial logit models to more complex nested logit models involving several levels of nesting and four or more market 76 segments. However, no clear consensus has yet emerged as to what explanatory variables should be included or how the various modes and sub-modes should be nested. In addition, even the most recent models still have not addressed a num- ber of problematic issues in a meaningful way. These include how to treat rental car use by non-residents of a region who often rent a car to meet local travel needs other than the air- port egress and later return access trip, and how best to account for the role of household income in the mode choice process. In addition to these technical considerations, there has been almost no attention given to how reliably existing mod- els predict air passenger access mode use when circumstance change from those prevailing when the model development data were collected. However, because the models are typi- cally used to predict mode use under very different condi- tions, including changes in the physical infrastructure or ground transportation services, there is a pressing need for more research into this aspect, as well as continuing research directed at improving the current state of practice. In contrast to air passenger mode choice models, there has been very little effort directed at developing airport employee mode choice models. The majority of metropolitan planning organizations model airport employee trips the same way as they model any other journey-to-work trips, if indeed they model them at all. The development of better airport em- ployee access models is a promising research opportunity. Finally, many existing regional travel models do not explicitly model airport trips, but treat them as general re- gional travel. Because of the unique characteristics of airport travel and the range of transportation options typically avail- able at airports, this is likely to give fairly poor predictions of airport mode use and the resulting vehicle trips. However, the likely magnitude of the error is not clear. Further research is needed to explore how well existing regional travel models account for airport trips and to provide guidance on how best to implement explicit modeling of airport access mode choice in the regional travel modeling process. CHAPTER NINE CONCLUSIONS AND FURTHER RESEARCH
