Demanda vs. Capacidad: Parámetros Recíprocos Básicos
Algunas Referencias Sobre la Demanda en Aviación
Dr. Antonio Trani
Air Transportation Systems Laboratory
Virginia Tech
Mayo 2009
Madas, M. A. and K. G. Zografos (2008). "Airport capacity vs. demand: Mismatch or mismanagement?"
Transportation Research Part A: Policy and Practice 42(1): 203-226.
Since well-publicized congestion and delay problems encountered by European and US airports
entered the political arena, there is an unprecedented pressure experienced by policy makers
upon investigating and adopting strategies for managing demand and allocating scarce airport
capacity. During the last few years, there is an ongoing policy debate within the European
Community to undertake further work for a drastically revised regulatory framework aiming to deal
with the scarcity of airport capacity through the efficient allocation of airport slots. One of the
primary policy concerns lies on the compatibility of alternative slot allocation strategies in different
airport settings. The objective of this paper is threefold: (i) to develop and apply a methodological
framework for the multi-criteria evaluation and selection of the most compatible slot allocation
strategy with respect to policy criteria and priorities in various airport settings, (ii) to examine the
applicability of policy compatibility results in various airport settings and their potential
acceptability from different industry stakeholders, and (iii) to provide policy recommendations for
European airport policy making and planning. © 2007 Elsevier Ltd. All rights reserved.
Le, L., G. Donohue, et al. (2008). "Optimum airport capacity utilization under congestion management: A
case study of New York LaGuardia airport." Transportation Planning and Technology 31(1): 93-112.
In the United States, most airports do not place any limitations on airline schedules. At a few
major airports, the current scheduling restrictions (mostly administrative measures) have not been
sufficiently strict to avoid consistent delays and have raised debates about both the efficiency and
the fairness of the allocations. With a forecast of 1.1 billion yearly air travelers within the US by
2015, airport expansion and technology enhancement alone are not enough to cope with the
competition-driven scheduling practices of the airline industry. The policy legacy needs to change
to be consistent with airport capacities. Flights on US airlines arrived late more often in the first
four months of 2007 than in any other year since the government began tracking delays, and
flight cancellations increased 91% over 2006. With a forecast of 1.1 billion yearly air travelers
within the US by 2015, airport expansion and technology enhancement alone are not enough to
cope with the competition-driven scheduling practices of the airline industry. Our research studies
how flight schedules might change if airlines were required to restrict their schedules to runway
capacity. To obtain these schedules, we model a profit-seeking, single benevolent airline whose
goal is to maintain current competitive prices and service as many current passengers as
possible, while remaining profitable. Our case study demonstrates that at Instrument
Meteorological Conditions (IMC) runway rates, the market can find profitable flight schedules that
reduce substantially the average flight delay to less than 6 minutes while simultaneously
satisfying virtually all of the current demand with average prices remaining unchanged. This is
accomplished through significant upgauging to high-demand markets.
Janic, M. (2008). "The future development of airports: A multidimensional examination." Transportation
Planning and Technology 31(1): 113-134.
The development of airports as the main component of air transport system infrastructure is
influenced by direct external developments (such as the globalisation and privatisation of the
airline industry, deregulation of domestic and liberalisation of international markets, increased
airline competition and volatile prices of the major airlines) and indirect external developments
(such as socio-economic forces and political events influencing the growth of air transport
demand). This paper examines the past, current and future development of airports through four
dimensions: (i) operational, sizing, and design of the airside and landside infrastructure; (ii)
economic; (iii) environmental; and (iv) social. The prospective future development of airports
through these dimensions is synthesised using cases from the European and the US air transport
systems.
Tam, M. L. (2007). Demand of rail mode in airport ground access market: A case study in Hong Kong,
Changdu, China, Institute of Electrical and Electronics Engineers Computer Society, Piscataway, NJ
08855-1331, United States.
This paper focuses on investigating the demand of the rail mode for airport ground access. Air
passenger traffic is experiencing ever-increasing levels of demand due to worldwide economic
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growth. This, in turn, is leading to roadway traffic congestion near airport regions. In order to deal
with the roadway traffic congestion problems, the development and enhancement of airport
railway systems is a must. However, planning the establishment of a railway system and also the
weighting given to a specific mode requires an intimate knowledge of passenger demand and
factors affecting this demand. Hong Kong International Airport (HKIA), which has its own airport
railway system, is chosen for the case study in this paper. With the use of the survey data
collected at HKIA, a multinormal logit model has been calibrated for identifying significant factors
affecting the demand of the rail mode. The results indicated that travel cost is the key factor
affecting air passenger ground access mode choice decisions. Party size and number of pieces
of baggage carried by an air passenger also affect the use of the rail mode. Based on the model
results, sensitivity tests were carried out so as to propose the optimal discount scheme for
increasing the utilization of the rail mode for accessing the airport. It was also noted that the
provision of connecting services to railway stations and the strategies to assist the passengers
with baggage are critical elements of a successful rail access to an airport. It is believed that the
calibrated model and proposed strategies can assist the planning of airport ground access
services at international airports. © 2007 IEEE.
Bhadra, D. and R. Schaufele (2007). "Probabilistic forecasts for aviation traffic at FAA's commercial
terminals: suggested methodology and example." Transportation Research Record(2007): 37-46.
Forecasting air travel in uncertain times is a challenging task. The effects of uncertainties
accompanied with usual errors emanating from estimation of demand prevent deterministic
forecasts from representing an uncertain future. The framework that is presented takes into
account uncertainty for which the nature and sources are unknown. A parametric distribution
fitting the past growth rates captures the probabilities associated with the outcomes representing
the future uncertainty at the airports. This process combined with Monte Carlo simulation is used
to generate probabilistic forecasts at the top 50 commercial airports in the United States. The
methodology is illustrated by using Hartsfield-Jackson Atlanta International Airport in Georgia.
Probabilistic forecasts provide an important tool for investment and personnel planning in
uncertain times.
Ashiabor, S., H. Baik, A. Trani (2007). "Logit models for forecasting nationwide intercity travel demand in
the United States." Transportation Research Record(2007): 1-12.
Nested and mixed logit models were developed to study national-level intercity transportation in
the United States. The models were used to estimate the market share of automobile and
commercial air transportation of 3,091 counties and 443 commercial service airports in the United
States. Models were calibrated with the use of the 1995 American Travel Survey. Separate
models were developed for business and nonbusiness trip purposes. The explanatory variables
used in the utility functions of the models were travel time, travel cost, and traveler's household
income. Given an input county-to-county trip demand table, the models were used to estimate
county-to-county travel demand by automobile and commercial airline between all counties and
commercial-service airports in the United States. The model has been integrated into a computer
software framework called the transportation systems analysis model that estimates nationwide
intercity travel demand in the United States.
Wei, W. and M. Hansen (2006). "An aggregate demand model for air passenger traffic in the hub-andspoke network." Transportation Research Part A: Policy and Practice 40(10): 841-851.
In this paper, we build an aggregate demand model for air passenger traffic in a hub-and-spoke
network. This model considers the roles of airline service variables such as service frequency,
aircraft size, ticket price, flight distance, and number of spokes in the network. It also takes into
account the influence of local passengers and social-economic and demographic conditions in
the spoke and hub metropolitan areas. The hub airport capacity, which has a significant impact
on service quality in the hub airport and in the whole hub-and-spoke network, is also taken into
consideration. Our demand model reveals that airlines can attract more connecting passengers in
a hub-and-spoke network by increasing service frequency than by increasing aircraft size in the
same percentage. Our research confirms the importance of local service to connecting
passengers, and finds that, interestingly, airlines' services in the first flight leg are more important
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to attract passengers than those in the second flight segment. Based on data in this study, we
also find that a 1% reduction of ticket price will bring about 0.9% more connecting passengers,
and a 1% increase of airport acceptance rate can bring about 0.35% more connecting
passengers in the network, with all else equal. These findings are helpful for airlines to
understand the effects of changing their services, and also useful for us to quantify the benefits of
hub airport expansion projects. At the end of this paper, we give an example as an application to
demonstrate how the developed demand model could be used to valuate passengers' direct
benefit from airport capacity expansion. © 2006 Elsevier Ltd. All rights reserved.
Thompson, T. R., M. L. Graham, et al. (2006). Estimating potential environmental constraints on aviation
growth, Wichita, KS, United States, American Institute of Aeronautics and Astronautics Inc., Reston, VA
20191, United States.
We address environmental constraints on aviation growth in two steps. First, noise and emission
models are linked with an existing model of the National Airspace System (NAS). Second, we
develop techniques to evaluate environmental constraints in terms similar to those used to
evaluate capacity constraints. Combined, these steps provide the ability to include environmental
considerations in quantitative, multi-dimensional system analysis of future NAS concepts. For the
first step, the approach consists of: 1) standard FAA noise and emissions-inventory models are
linked to Airspace Concept Evaluation System (ACES) simulation outputs; 2) appropriate
modifications are made to ACES outputs to incorporate all information needed by the
environmental models (e.g., specific airframe and engine data); 3) noise and emissions
calculations are performed for all traffic and airports in the study area for each of several
scenarios; and 4) the impacts of future scenarios are compared to the current NAS scenario. For
the second step, the approach consists of: 1) identifying possible quantitative environmental
goats in fuel efficiency and noise; 2) computing fuel-efficiencies and noise a future scenario; and
3) estimating the traffic reductions that would be necessary to meet the environmental goals. This
paper also provides the results of end-toend, proof-of-concept runs of the integrated ACES and
environmental modeling capability. These results demonstrate that if no changes are made to
elements of the NAS, aviation growth is likely to be impeded by substantial environmental
constraints. Pilot calculations of these constraints in terms of unsatisfied demand indicate that the
environmental constraints may be similar in magnitude to capacity constraints.
Trani, A. A., H. Baik, et al. (2006). Nationwide impacts of very light jet traffic in the future Next Generation
Air Transportation System (NGATS), Wichita, KS, United States, American Institute of Aeronautics and
Astronautics Inc., Reston, VA 20191, United States.
This paper describes a methodology to predict on-demand air taxi services using emerging Very
Light Jets (VLJ) technology in the future National Air Transportation System (NAS). The paper
describes airspace and airport impacts of VLJ traffic considering an improved Next Generation Air
Transportation System (NGATS). The analysis presented fits within the framework of the
Transportation Systems Analysis Model (TSAM) developed by the Air Transportation Systems
Laboratory at Virginia Tech for NASA Langley Research Center. TSAM uses traditional air
transportation systems engineering techniques to: 1) predict the number of intercity trips
generated in the country based on socio-economic factors, 2) distribute these trips across the
country, 3) predict the most likely modes of transportation used to execute these trips, 4) predict
flights and trajectories associated with air transportation trips, and 5) predict impacts of the
intercity trips generated in the National Airspace System (NAS). Copyright © 2006 by the
American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
Dollyhigh, S., J. Smith, et al. (2006). Projecting future scheduled airline demand, schedules and NGATS
benefits using TSAM, Wichita, KS, United States, American Institute of Aeronautics and Astronautics Inc.,
Reston, VA 20191, United States.
The Transportation Systems Analysis Model (TSAM) developed by Virginia Tech's Air
Transportation Systems Lab and NASA Langley can provide detailed analysis of the effects on
the demand for air travel of a full range of NASA and FAA aviation projects. TSAM has been used
to project the passenger demand for very light jet (VLJ) air taxi service, scheduled airline demand
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growth and future schedules, Next Generation Air Transportation System (NGATS) benefits, and
future passenger revenues for the Airport and Airway Trust Fund. TSAM can project the resulting
demand when new vehicles and/or technology is inserted into the long distance (100 or more
miles one-way) transportation system, as well as, changes in demand as a result of fare yield
increases or decreases, airport transit times, scheduled flight times, ticket taxes, reductions or
increases in flight delays, and so on. TSAM models all long distance travel in the contiguous U.S.
and determines the mode choice of the traveler based on detailed trip costs, travel time, schedule
frequency, purpose of the trip (business or non-business), and household income level of the
traveler. Demand is modeled at the county level, with an airport choice module providing up to
three airports as part of the mode choice. Future enplanements at airports can be projected for
different scenarios. A Fratar algorithm and a schedule generator are applied to generate future
flight schedules. This paper presents the application of TSAM to modeling future scheduled air
passenger demand and resulting airline schedules, the impact of NGATS goals and objectives on
passenger demand, along with projections for passenger fee receipts for several scenarios for the
FAA Airport and Airway Trust Fund.
Baik, H., S. Ashiabor, and A. Trani (2006). "Development of an airport choice model for general aviation
operations." Transportation Research Record(1951): 17-27.
The general aviation airport choice model is used to estimate general aviation (GA) person trips
and number of aircraft operations through a set of airports given initial trip demand (GA person
trips) from a set of counties. A pseudogravity model embedded in the model is used to distribute
the intercounty person trips to the set of airports. The interairport person trips are then split into
person trips by aircraft type (single, multiple, or jet engine). To split the trips, an attractiveness
factor is developed on the basis of average occupancy, level of use, a distance distribution factor,
and number of operations of each aircraft type. The person trips by aircraft type are then
converted to aircraft operations with the use of occupancy factors for each aircraft type. The final
model output is the number of aircraft operations by each aircraft type, in the form of three
interairport trip tables. The estimated GA operations provide a means of assessing the impact of
GA activities on the National Airspace System. The model output may also be used to assess the
viability of GA aircraft as a competitive mode of transportation for intercity travel.
Hansen, M. and Y. Zhang (2005). "Operational consequences of alternative airport demand management
policies case of LaGuardia Airport, New York." Transportation Research Record(1915): 95-104.
The current demand management policy at LaGuardia Airport (LGA) New York, must be changed
in 2007 under the provision of the Wendell H. Ford Aviation Investment and Reform Act for the
21st Century of April 2000 (AIR-21). As a preliminary step for developing a new policy, this study
considered how past policies, along with other factors, have affected operational performance at
LGA. The interaction between LGA and the rest of the aviation system was also investigated by
estimating simultaneous equations of average delay for LGA and the National Airspace System
(NAS) by using two-stage least squares. The results demonstrate that the arrival delay impact of
AIR-21 on LGA was in the form of Increased Ground Delay Program holding and that although
delay increased markedly under AIR-21, there were also observable improvements in the ability
of LGA to handle traffic. Furthermore, on the basis of the simultaneous equations analysis, it was
found that 1 min of arrival delay at LGA causes about 2 min of delay elsewhere in the NAS,
suggesting that demand management at LGA is a national rather than a local issue.
Cooke Jr, S. A., J. K. Viken, et al. (2005). Transportation Systems Analysis and Assessment (TSAA) for
the Small Aircraft Transportation System (SATS) Project, Arlington, VA, United States, American Inst.
Aeronautics and Astronautics Inc., Reston, VA 20191-4344, United States.
The Small Aircraft Transportation System (SATS) Project is a five-year effort to research and
demonstrate a core set of operational procedures and technologies that will enable an alternative
mode of transportation using a new class of small aircraft and our nation's existing small airports.
The Transportation Systems Analysis and Assessment (TSAA) team is the sub-element of the
SATS project that is responsible for analyzing and assessing the political, operational, socioeconomical and technical impact of the SATS operating capabilities. The TSAA team consisting
of members from industry, academia and non-profits, has conducted a series of extensive
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transportation systems analysis, analytical and human-in-the-loop simulations, sensitivity studies
and market analysis to determine the demand for travel via SATS mode, the impact of increased
SATS traffic in the National Airspace System (NAS), the Business Case for SATS and the
national cost-benefits of SATS. The key objective of the TSAA is to communicate the value and
benefits of SATS operations to the traveler, service providers, small communities and key political
and business decision makers. A Transportation Systems Analysis Model (TSAM) based on
Systems Dynamics has been developed that employs a multi-step transportation planning
process to forecast the market share of US travel via the commercial hub and spoke system,
automobile and SATS modes. The environmental, emissions, fuel consumption, noise impacts as
well as the national mobility and timesavings improvements are also evaluated. A Monte Carlo Air
Taxi Simulation (MCATS) tool has been developed to analyze the feasibility and several business
aspects of a small aircraft transportation system serviced by an air taxi business model. A series
of fast-time simulations and controller simulations have been performed to evaluate the safety,
capacity and efficiency impacts in the NAS en route sectors of increased SATS traffic coupled
with forecasted commercial traffic in the years 2010. This paper presents and comprehensive
collection of the methodologies, analysis, simulations, studies and final findings of the SATS
TSAA team. These quantitative and qualitative results form the basis for existing and future
strategic and tactical political and business decisions that have the potential to enable new
business models for increased air mobility, economic growth and improved quality of life for our
nation. The results will hopefully inspire public understanding of the SATS concept, influence
current and future planning and investment decisions and support critical legislative and
regulatory policies.
Stamatopoulos, M. A., K. Zografos, et al. (2004). "A decision support system for airport strategic
planning." Transportation Research Part C: Emerging Technologies 12(2): 91-117.
This paper describes an integrated set of models for the estimation of the capacity of an airfield
and the associated delays. The aim is to develop a decision support tool suitable for airport
planning at the strategic level. Thus, the emphasis is on obtaining reliable approximations to the
quantities of interest quickly and with a limited set of inputs. The models account for the dynamic
characteristics of airfield capacity and demand, as well as for some stochastic aspects of airfield
operations. They are sensitive to airfield geometry, the operational characteristics of the airfield
and of the local air traffic control system, and the characteristics of the local air traffic demand for
airport access and services. Through its integrated structure, the decision support tool can
account for interactions among operations at different parts of the airfield. © 2003 Elsevier
Ltd. All rights reserved.
Le, L., G. Donohue, et al. (2004). "Auction-based slot allocation for traffic demand management at
hartsfield Atlanta International Airport: A case study." Transportation Research Record(1888): 50-58.
Ongoing research is described for an auction model, a hybrid demand management approach for
congested airports. This approach is intended to optimize the use of airport time slots by
maximizing passenger throughput with safe capacity, decreasing congestion, and less delay. The
two submodels mathematically formulate conflicting optimization problems of efficiency-driven
airport regulators and cost-driven airlines. By ranking key factors such as monetary bidding, flight
origin-destination pairs, enplanement capability, and airlines' previous investments, a framework
is presented that is open to many design alternatives. Two design alternatives are analyzed in a
case study of Hartsfield Atlanta International Airport, Georgia, to compare different allocation
schemata and resulting airport performance. The performance analysis used a queuing model
simulation. By varying weighting coefficients for bid vectors, it is proposed that the effects of
administrative coordination and market force on outcomes of the auction process could be
monitored to achieve airport-specific benefits. It is also suggested that the conventional auction
format that uses monetary bidding alone could lead to potential distortions of the marketplace and
fail to meet air transportation officials' concerns about the efficient use of national resources and
policy makers' concerns about market structure and competitiveness. Future work will enlist the
input from both airlines and airports.
Janic, M. (2004). "Expansion of airport capacity at London heathrow airport." Transportation Research
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Record(1888): 7-14.
Civil aviation has been confronted with the problem of matching its capacity to growing demand
long term. This has been a particularly important issue at some large European and U.S. airports
where increasing operational, economic, and, particularly, environmental constraints have
affected expansion and development. The long-term matching of capacity to demand at London
Heathrow Airport in England is discussed. This analysis includes predicting airport demand
relative to annual number of aircraft movements and number of passengers, designing solutions
for providing capacity, and generating scenarios for long-term matching of capacity to demand.
The results indicate that until the year 2020 the airport will permanently struggle with congestion
both airside and landside.
Zografos, K. G. and M. A. Madas (2003). "Critical Assessment of Airport Demand Management Strategies
in Europe and the United States Comparative Perspective." Transportation Research Record(1850): 4148.
The ever-tighter mismatch between the demand and supply of airport services has triggered
policy discussions that bring to the forefront a challenging dilemma for decision makers and the
various Stakeholding groups in the airport domain: demand management or capacity
enhancement? There are two solutions in the effort to reduce gridlock in the air transport system to expand capacity, and to diminish or handle demand through time and space. One part of the
answer lies with technology and operations aiming at building capacity and another with
balancing and handling demand. Since the last decade of continuously increasing air traffic
congestion, demand management strategies have gained increasing acceptance by airport
authorities and policy makers as a potential vehicle of handling demand - by limiting in some way
the demand for access to busy airfields or to congested airspace or by modifying the spatial and
temporal distribution of demand, or by doing both. A critical review was done of the
developments, practices, and research activities in Europe and the United States toward
confronting the well-known aviation capacity gridlock. A triplet of analysis formed the base: the
current state of affairs pertaining to the demand and growth patterns and prospects vis-a-vis
supply-side developments; the discussion of the aviation capacity gridlock; and an in-depth
analysis and critical assessment of the alternative demand-side solutions under the spectrum of
all potential enhancement aspects (i.e., administrative, economic, hybrid measures).
Trani, A. A., H. Baik, et al. (2003). "Integrated Model for Studying Small Aircraft Transportation System."
Transportation Research Record(1850): 1-10.
A systems engineering methodology was used to study the National Aeronautics and Space
Administration's (NASA's) Small Aircraft Transportation System (SATS) concept as a feasible
mode of transportation. The proposed approach employs a multistep intercity transportation
planning process executed inside a Systems Dynamics model. Doing so permits a better
understanding of SATS impacts to society over time. The approach is viewed as an extension to
traditional intercity transport models through the introduction of explicit demand-supply causal
links of the proposed SATS over the complete life cycle of the program. The modeling framework
discussed is currently being used by the Virginia SATS Alliance to quantify possible impacts of
the SATS program for NASA's Langley Research Center. There is discussion of some of the
modeling efforts carried out so far and of some of the transportation modeling challenges facing
the SATS program ahead.
Lythgoe, W. F. and M. Wardman (2002). "Demand for rail travel to and from airports." Transportation
29(2): 125-143.
Rail access to airports is becoming increasingly important for both train operators and the airports
themselves. This paper reports analysis of inter-urban rail demand to and from Manchester and
Stansted Airports and the sensitivity of this market segment to growth in air traffic and the cost
and service quality of rail services. The estimated demand parameters vary in an expected
manner between outward and inward air travellers as well as between airport users and general
rail travellers. These parameters can be entered into the demand forecasting framework widely
used in the rail industry in Great Britain to provide an appropriate means of forecasting for this
otherwise neglected market segment. The novel features of this research, at least in the British
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context, are that it provides the first detailed analysis of aggregate rail flows to and from airports,
it has disaggregated the traditional generalised time measure of rail service quality in order to
estimate separate elasticities to journey time, service headway and interchange, and it has
successfully explored departures from the conventional constant elasticity position.
Devoto, R., C. Farci, et al. (2002). Analysis and forecast of air transport demand in Sardinia's airports as
a function of tourism variables, Seville, Spain, WIT Press, Southampton, SO40 7AA, United Kingdom.
The potential of an econometrics approach for forecasting air transport demand is examined. The
aim is to identify and select the most significant variables for multivariable linear regression
models. Each independent variable has been evaluated by means of ARIMA models after
rendering the historical series stationary. The variables for the different cases examined have
been chosen using Student's t-test and the correlation matrix to determine their level of
significance and of correlation. The resulting models have been tested on three airports in
Sardinia (Cagliari, Olbia and Alghero) in order to identify the most suitable and characteristic
variables for representing air transport demand. Time series for annual passenger movements
have been constructed for each airport expressed in absolute terms and index number.
Ulukaya, M. G., G. S. Ito, et al. (2000). Overcoming taxiway realignment constraints at LAX, San
francisco, CA, USA, American Society of Civil Engineers, Reston, VA, USA.
Besides increasing capacity demands, Los Angeles International Airport faces the problem of
separation between the operations of the Taxiway `C' and Taxiway `B'. This creates hindrance in
the efficient operation of the airport. To overcome these problems, a realignment of Taxiway is
proposed which would solve the problem of this congested and complicated site.
Ghobrial, A. and A. Kanafani (1995). "Quality-of-service model of intercity air-travel demand." Journal of
Transportation Engineering 121(2): 135-140.
An econometric model is estimated for intercity passenger demand using postderegulation data.
The model incorporates some quality-of-service measures as explanatory variables. These
include flight frequency during peak and off-peak periods, aircraft size (i.e., number of seats), and
travel time. The results suggest that demand is elastic with respect to airfare, and is highly
dependent on flight schedule and travel time. It seems that frequency and route planning will
continue to be challenges for the airlines, and that the solutions are very much market specific.
They will depend on, among other things, the predominant trip purpose (business or
nonbusiness), and the capacity constraints that affect the utilization of specific airports.
Hassounah, M. I. and G. N. Steuart (1993). Demand for aircraft gates: 26-33.
Demand for aircraft gates, which is defined as the number of aircraft expected to require the
service provided at a terminal building at any given time during one day's operation, depends on
flights scheduled and their actual behavior relative to those schedules. The schedules provide a
deterministic element to the process of generating the actual number of aircraft at gates, and
deviation from these schedules provides a stochastic element to the process. A model that
incorporates these two elements has been developed to estimate gate requirements at airports.
The results of applying the model to an actual operation of aircraft gates have demonstrated the
ability of the model to describe gate occupancy as a function of time of day with reasonable
accuracy. The results have also shown that a common gate use strategy (i.e., first-come, firstserved discipline) requires fewer gates than strategies under which the use of gates is restricted
to flights of a particular air carrier or sector. Furthermore, it has been demonstrated, given a
scheduling practice involving bank operations, how the time interval between banks influences
the requirement for gates.
Odoni, A. R. (1991). Issues in modeling a national network of airports, Phoenix, AZ, USA, Publ by IEEE,
Piscataway, NJ, USA.
The modeling of networks consisting of a large number of geographically dispersed airports is
considered. The need for models of this type has become clear recently as a result of growing
systemwide congestion of air traffic, the propagation of delays from one airport to others, and the
desire, at the national policy level, to intelligently allocate scarce federal resources among
8
competing alternatives and local airport projects. Some fundamental difficulties associated with
network models of this type are examined. Important issues include problem size and data
requirements; the probabilistic and dynamic nature of the airport system's demand and capacity;
the combinatorially explosive number of possible network states and the resulting need for careful
statistical sampling and analysis; the sensitivity of computational performance to the level of detail
in the network model; the difficulty of preparing demand scenarios that predict future connections
between pairs of airports; and user requirements for model robustness, portability, and
transparency. These issues are discussed and illustrated in some detail, including references to
specific existing network models of the ATC (air traffic control) system.
Innes, J. D. and D. H. Doucet (1990). "Effects of access distance and level of service on airport choice."
Journal of Transportation Engineering 116(4): 507-516.
Aviation growth over the last two decades has caused traffic volumes at many airports to attain
near-capacity levels. Demand management systems have been used to increase throughput and
alleviate congestion where practical. However, airports continue to be increasingly congested.
Due to restricted land availability as well as environmental and community concerns, the potential
for airport expansion is often limited, and airport authorities increasingly face the prospect of
relocating airports. Obviously, the ability of the airport to serve its market is affected by such a
relocation. This paper examines the importance of airport proximity as well as the effects of levelof-service factors on alternate airport choice. Disaggregate modeling techniques were used in the
identification of factors affecting the choice of alternate airports in a limited geographical area
(northern New Brunswick, Canada). The research demonstrates the significance of level-ofservice variables in the airport-choice decision. Air travelers had a strong preference for jet
aircraft and were willing to travel significant ground distances in order to reach an airport offering
jet service. The analysis results clearly show that this was the single most important variable in
the airport-choice decision. Other significant level-of-service variables were flying-time difference
and whether a direct flight to destination was available.
Tilles, R. D. (1978). "AIRPORT TRAFFIC GENERATION MODEL." EUROMICRO Journal (European
Association for Microprocessing and Microprogramming): 428-447.
A model using FORTRAN was created to forecast the demand imposed on various ground
transportation facilities on and off the airport. The model accounts for the complex
interrelationships involved in airport ground traffic demand estimation, and was used to forecast
ground access demand in planning a new airport for Tehran, Iran. The Airport Traffic Generation
Model has proven to be a good compromise between hand calculations and complex simulation
models. The complete model output is useful in selecting airport sites, planning new airports and
in major expansion projects. Output from the off-airport sections of the model can be used to
examine ground access constraints at existing airports.
Lin, F.-B. (1977). "AIRPORT CHOICE IN LOW DEMAND REGION." American Society of Civil Engineers,
Transportation Engineering Journal 103(6): 711-727.
Air traveling by residents of the core area of St. Lawrence County, New York is characterized by
long ground access distance and is subjected to influences by airports across the border in
Canada. To provide a means for evaluating potential impacts of new or improved regional airports
which are to serve the area, a study is conducted to model the choice of competing airports by
the air passengers. The study is based on data collected from a telephone survey of 16. 6% of
the households. A binary choice model is found to be able to explain the choice behaviors
adequately. The model does not have to rely on large data base. It is theoretically sound and
easy to apply.
De Neufville, R. (2008). "Low-cost airports for low-cost airlines: Flexible design to manage the risks."
Transportation Planning and Technology 31(1): 35-68.
Airport planning is shifting from the traditional pattern - driven by long-term point forecasts, high
standards, and established clients - to that of recognizing great forecast uncertainty, many
standards and changeable clients. This is a consequence of economic deregulation of aviation
and the rise of low-cost airlines. Low-cost airlines are becoming significant factors in airport
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planning. Their requirements differ from those of 'legacy'carriers. They drive the development of
secondary airports and cheaper airport terminals. They catalyze 'low-cost airports' around the
'legacy main airports' built for the 'legacy airlines'. This paper proposes a flexible design strategy
to deal with the uncertainty of this dynamic. This differs significantly from traditional airport master
planning. It builds flexibility into the design, to enable airports to adjust to changes in the type,
needs and location of traffic. The case of Portugal illustrates the current risks, and indicates how
flexible design could manage uncertainties and maximize expected value.
de Neufville, R. and S. C. Belin (2002). "Airport passenger buildings: Efficiency through shared use of
facilities." Journal of Transportation Engineering 128(3): 201-210.
This paper provides a comprehensive guide to the design of shared facilities. Shared facilities
serve many users (aircraft, airlines, or types of services) in several functions (arrivals, departures,
international and domestic, and so on). They significantly increase the utilization of facilities, thus
reducing the amount needed for any level of traffic. They also increase the flexibility of the
building, thus enabling it to accommodate easily to variations in traffic composition (the fractions
associated with specific airlines or international and domestic services). Shared facilities reduce
capital expenditures by up to 30%, and correspondingly increase the return on the investment.
Two main factors motivate the use of shared facilities. One is peaking; that is, variations in the
levels of traffic (either in hours or a day). The other is uncertainty in the timing of the traffic (either
in the short run or in the long run). The paper details the appropriate analyses in each instance. It
presents analytic results showing that the design of passenger buildings should normally include
shared space, swing gates, and shared facilities that buffer uncertain demands.
de Neufville, R. and J. R. Guzman (1998). "Benchmarking for design of major airports worldwide." Journal
of Transportation Engineering 124(4): 391-395.
This note presents, for the first time, the concept of benchmarking of airports from the perspective
of designers and planners. Benchmarking is valuable for three reasons: it provides basic data
otherwise difficult to obtain, it defines world class standards for facilities, and it identifies priorities
for improving the physical design at individual airports. Effective benchmarking is focused on
objective data of capacity or performance that can be measured and observed in widely different
operations, rather than on data that is subjective or derived from widely different accounting
practices. The note illustrates the approach by comparing availability of airside and landside
facilities at comparable major airports worldwide - those that handle between 12 and 26 million
passengers each year, and for which data were available. This initial comparison underlines the
fact that airports worldwide differ enormously in the relative amount of facilities they provide, and
suggests which airports might require additional investments to reach the best worldwide levels.
An application of benchmarking to the Mexico City International Airport demonstrates the
usefulness of the concept.
De Neufville, R. and L. J. Mira (1974). "OPTIMAL PRICING POLICIES FOR AIR TRANSPORT
NETWORKS." Transportation Research 8(3): 181-192.
This paper suggests how marginal cost pricing can be used to optimize the level of service
provided by air transport. The analysis indicates that active governmental intervention is generally
necessary to achieve a social optimum; that fixed prices are largely ineffective by themselves at
maximizing either the public good or private gain to the airlines; that the governmental
intervention should involve either taxes or subsidies, depending on the kind of externalities that
exist, and that these should be applied differentially to the passengers and airlines; and that it is
optimal, for both the public and the airlines, to fly aircraft essentially full and that it would be
desirable to institute a system of flexible prices for off-peak travel so that this could be achieved.
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