Peter Vovsha

Air Passenger Preferences for Choice of Airport and Ground Access Mode in the New York City Metropolitan Region

In current practice, regional models are limited in their capability to analyze policies involving changes and improvements to airports (and their services) and ground access transportation. Typically, airports are treated only as employment centers or as special generators. Important and distinct features of air passenger travel affecting trip distribution and mode choice are rarely modeled explicitly. This paper presents the development of a joint airport and ground access mode choice model for the New York City metropolitan region based on an extensive survey of airport users. Unlike travel to and from most U.S. cities, air passengers flying to and from the New York region face a nontrivial choice of airports and ground access modes (including premium transit options). A nested logit model was formulated with airport choice at the upper level and ground access mode choice at the second level; however, a multinomial logit model was found to be statistically preferable. Results indicate that air passenger travel behavior is significantly different for business and nonbusiness travelers. Overall, willingness to pay for trips to and from the airport is much higher than for regular intracity trips. Average yield, access time, and access cost are the most important determinants of air passengers choice; demographics and trip characteristics are also significant. The developed tool was used for a comprehensive study of airport development alternatives in the New York region and is seen as the platform for additional data development and model extensions for future studies of air passenger service planning in the New York megaregion.

Network Equilibrium with Activity-Based Microsimulation Models: The New York Experience

Travel demand models and network simulation models are distinct sets of procedures that are combined and interact within the framework of regional transportation modeling systems. Conventional four-step models have numerous limitations compared with more advanced activity-based microsimulation models, primarily with respect to internal consistency and detailed behavioral realism. However, two of the remaining advantages of four-step models are an established theory and an effective set of practical rules for achieving global network equilibrium so that travel time and cost simulated in the networks exactly correspond to the demand (trip tables) generated by the model. Nonetheless, this issue remains less explored and somewhat obscure for activity-based models. These models have a more complicated analytical structure compared with four-step models, which makes it difficult to derive equilibrium conditions in a rigorous theoretical manner. In addition, implementation of an activity-based model requires microsimulation of individual outcomes in the form of “crisp” discrete choices that is very different from the summation of fractional probabilities implemented in conventional models. This paper documents the results of testing various equilibrium strategies implemented with the New York City activity-based microsimulation regional travel demand model used by the New York Metropolitan Transportation Council. The purpose of the paper is twofold. First, it is intended to outline some fundamental research directions and extensions of the network equilibrium theory to cover activity-based microsimulation models in a more rigorous way. Second, it describes realistic levels of convergence that can be achieved with activity-based microsimulation models in practice and establishes practical rules and protocols for using these types of models for different projects and policies.