Model to Forecast Air Passenger Demand Across a System of Commercial Service Airports (Network Air Demand Analysis Model (NADAM))
Research Problem Statement:
The 517 commercial service airports according to the National Plan of Integrated Airport Systems are expected to require $41 billion in capital developments over a five year period. The large and medium hub airports serve 89% of the scheduled passenger enplanements. The Airport Improvement Program (AIP) supports airport safety, capacity, and environmental projects to thousands of airports across the nation. The Operational Evolution Partnership (OEP) has focused on key airport developments at the nations busiest airports along with coordinated air traffic management initiatives and investments. During the past decade, capacity constraints across the National Aviation System (NAS) have become progressively more binding as the secular trend of demand presses against the NAS’s component limits. The FAA, individual states and communities, the airlines, and the ultimate consumer of air transport services have practical and competitive constraints on the commitment of financial resources to the air transport system and the services it provides. Since resources are finite it behooves the federal government to allocate the discretionary funds to those projects which are most likely to serve the most potential air passengers and offer the most value to them. Communities regularly bring proposals to the federal government expecting the FAA to fund new and expanded airport facilities that may already be competitively served and the investment of infrastructure funds may have little or no effect on the stimulation of demand or the improvement of air transport services at that locale.
The state and regional transportation planning agencies, airports, FAA, and DOT need an objective air passenger market based method to assess the proposed needs for airport system developments across a constellation of airport facilities imbedded within the landscape of the overall communities they serve. Numerous models have been developed for forecasting aircraft operations at individual airports and by extension across the NAS based on past patterns of use. Current practice is yet to integrate in a systematic framework the effects of changing geographical demographics and industry structures, and the evolving (and sometimes experimental) air service patterns of airlines. The NAS requires both geographically fixed and flexible airport and air traffic management infrastructure investments which are balanced, resilient, timely, and affordable. Like any investor the individual airports and the FAA need to undertake their due diligence and invest in projects and programs that provide prudent payoffs. Yet as noted above there is not an integrated framework for systematically evaluating consumer and market needs. The current state of the NAS relies upon the individual requests of local airports which are evaluated in an episodic, piecemeal, and patchwork fashion. FAA’s own internal investment planning for air traffic control infrastructure under its NextGen also requires input as to the valuation that end users place on air traffic management capabilities in order to properly design and invest in an efficient and cost beneficial manner. The funding of this task provides a vehicle for the airport community to support and influence the future shape and texture of the NAS’ most important airport development requirements.
Develop or refine a geographic based model and associated databases to forecast originating demand for air passenger transport services. The model should be structured to differentiate amongst air passenger, air service, and fare characteristics, and ground accessibility factors.
II. Research Proposed:
Phase 1: Conduct literature review, develop a schematic pilot model structure, demonstrate simple model application.
Phase 2: Develop detailed model and database structures to be implemented in a web based environment. Model should be scalable to different geographical regions for application in national, state, and regional studies.
Phase 3: Training, refine documentation, dissemination, and technical support of model.
Phase 4: Refresh and revise model and databases (to be funded by DOT/FAA and/or public consortium?).
III. Estimate of the Problem Funding and Research Period:
Phase 1: $ 150,000
Phase 2: $ 500,000
Phase 3: $ 100,000
Phase 4: $ 100,000 / year
Phase 1: 9 months
Phase 2: 15 months
Phase 3: 3 months
Phase 4: indefinite
IV. Urgency and Payoff Potential:
FAA receives numerous requests for discretionary funds for airport capacity projects. Improving the demand forecasting process to explicitly account for system effects and options enables the federal government to make smarter more cost effective commitments while minimizing major misallocations of fixed resources that provide little benefit or service. This management tool can increase the effective return on investment to the NAS and provide a rational basis for minimizing the earmarking of scare AIP resources. Other applications of the model may be to estimate the effects of community air service changes on locally realized passenger demand or the analysis of the effects of capacity constraints or demand management strategies.
V. Related Research:
ACRP Synthesis 11-03 / Topic S03-04 Airport System Planning Practices
FAA National Plan of Integrated Airport Systems
FAA Operational Evolution Partnership
JPDO NextGen Exhibit 300, Integrated Work Plan,