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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2010

Fundamental Travel Demand Model Example

Instances of transportation models are abundant and detailed "how to" instruction is available in the form of transportation software help documentation. The purpose of this paper is to look at the fundamental inputs required to build a transportation model by developing an example passenger travel demand model. The example model reduces the scale to a manageable size for the purpose of illustrating the data collection and analysis required before the first step of the model begins. This aspect of the model development would not reasonably be discussed in software help documentation (it is assumed the model developer comes prepared). Recommendations are derived from the example passenger travel demand model to suggest future work regarding the data collection and analysis required for a freight travel demand model.

Hanssen, Joel↗
NASA NTRS1971

Study of an intraurban travel demand model incorporating commuter preference variables

The model is based on the substantial travel data base for the nine-county San Francisco Bay Area, provided by the Metropolitan Transportation Commission. The model is of the abstract type, and makes use of commuter attitudes towards modes and simple demographic characteristics of zones in a region to predict interzonal travel by mode for the region. A characterization of the STOL/VTOL mode was extrapolated by means of a subjective comparison of its expected characteristics with those of modes characterized by the survey. Predictions of STOL demand were made for the Bay Area and an aircraft network was developed to serve this demand. When this aircraft system is compared to the base case system, the demand for STOL service has increased five fold and the resulting economics show considerable benefit from the increased scale of operations. In the previous study all systems required subsidy in varying amounts. The new system shows a substantial profit at an average fare of $3.55 per trip.

Holligan, P. E.↗
NASA NTRS1972

World Air Travel Demand, 1950-1980

Total world scheduled air passenger traffic carried by the airlines of the International Civil Aviation Organization (ICAO), excluding the U.S.S.R., increased from 17.4 billion passenger miles in 1950 to 237.4 billion in 1970. This represents an average annual growth rate of 14% during the past two decades. The U.S.S.R. became a member of ICAO in 1970, and Aeroflot - the only Russian airline - reported 49 billion passenger miles for 1970. This traffic, which encompasses both domestic and international travel as well as some nonscheduled flights, is not included in the ICAO world totals shown in this report.

Sarames, G. N.↗
NASA NTRS2015

Understanding Air Transportation Market Dynamics Using a Search Algorithm for Calibrating Travel Demand and Price

This paper presents a search algorithm based framework to calibrate origin-destination (O-D) market specific airline ticket demands and prices for the Air Transportation System (ATS). This framework is used for calibrating an agent based model of the air ticket buy-sell process - Airline Evolutionary Simulation (Airline EVOS) -that has fidelity of detail that accounts for airline and consumer behaviors and the interdependencies they share between themselves and the NAS. More specificially, this algorithm simultaneous calibrates demand and airfares for each O-D market, to within specified threshold of a pre-specified target value. The proposed algorithm is illustrated with market data targets provided by the Transportation System Analysis Model (TSAM) and Airline Origin and Destination Survey (DB1B). Although we specify these models and datasources for this calibration exercise, the methods described in this paper are applicable to calibrating any low-level model of the ATS to some other demand forecast model-based data. We argue that using a calibration algorithm such as the one we present here to synchronize ATS models with specialized forecast demand models, is a powerful tool for establishing credible baseline conditions in experiments analyzing the effects of proposed policy changes to the ATS.

Kumar, Vivek↗
NASA NTRS1978

Demand modelling of passenger air travel: An analysis and extension, volume 2

Previous intercity travel demand models in terms of their ability to predict air travel in a useful way and the need for disaggregation in the approach to demand modelling are evaluated. The viability of incorporating non-conventional factors (i.e. non-econometric, such as time and cost) in travel demand forecasting models are determined. The investigation of existing models is carried out in order to provide insight into their strong points and shortcomings. The model is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed. In addition this volume contains two appendices which should prove useful to the non-specialist in the area.

Jacobson, I. D.↗
NASA NTRS1978

Demand modelling of passenger air travel: An analysis and extension. Volume 1: Background and summary

The framework for a model of travel demand which will be useful in predicting the total market for air travel between two cities is discussed. Variables to be used in determining the need for air transportation where none currently exists and the effect of changes in system characteristics on attracting latent demand are identified. Existing models are examined in order to provide insight into their strong points and shortcomings. Much of the existing behavioral research in travel demand is incorporated to allow the inclusion of non-economic factors, such as convenience. The model developed is characterized as a market segmentation model. This is a consequence of the strengths of disaggregation and its natural evolution to a usable aggregate formulation. The need for this approach both pedagogically and mathematically is discussed.

Jacobson, I. D.↗
NASA NTRS1972

Study of short haul high-density V/STOL transportation systems, volume 1

The relative advantages of STOL aircraft concepts were examined by simulating the operations of a short haul high-density intercity STOL system set in two arenas, the California corridor and the Chicago-Detroit-Cleveland triangle, during the 1980 time period. The study was constrained to the use of three aircraft concepts designated as the deflected slipstream turboprop, externally blown flap, and augmentor wing turbofan configurations. The projected demographic, economic, travel demand, and travel characteristics of the representative arenas were identified. The STOL airline operating scenarios were then formulated and through the use of the aerospace modal split simulation program, the traveler modal choices involving alternative STOL concepts were estimated in the context of the total transportation environment for 1980. System combinations that presented the best potential for economic return and traveler acceptance were then identified for each STOL concept.

Solomon, H. L.↗
NASA NTRS2003

Consumer Expectations of Capacity Constrains and Their Effect on the Demand for Multi-Class Air Travel

This paper argues that a consumer's decision on ticket class takes into account the expected likelihood of obtaining a seat in a particular class which, in turn, partially depends on an optimum "transaction cost". Taking into account the preferences of the consumer and the information that the consumer is endowed with, the consumer will select a ticket that includes its own optimal transaction cost. This motivates the inclusion of the capacity constraint as a proxy independent variable for these consumer expectations This then forms the basis of a model of air-travel demand with specific reference to Australia. A censored likelihood function allowing for correlation in the disturbance term across k classes is introduced. The correlation in the disturbances arises as a result of the interdependence of the capacity constraints in k different ticket classes on each flight.

Battersby, Bryn D.↗
NASA NTRS1989

California air transportation study: A transportation system for the California Corridor of the year 2010

To define and solve the problems of transportation in the California Corrider in the year 2010, the 1989 California Polytechnic State University Aeronautical Engineering Senior Design class determined future corridor transportation needs and developed a system to meet the requirements. A market study, which included interpreting travel demand and gauging the future of regional and national air travel in and out of the corridor, allowed the goals of the project to be accurately refined. Comprehensive trade-off studies of several proposed transporation systems were conducted to determine which components would form the final proposed system. Preliminary design and further analysis were performed for each resulting component. The proposed system consists of three vehicles and a special hub or mode mixer, the Corridor Access Port (CAP). The vehicles are: (1) an electric powered aircraft to serve secondary airports and the CAP; (2) a high speed magnetic levitation train running through the CAP and the high population density areas of the corridor; and (3) a vertical takeoff and landing tilt rotor aircraft to serve both intercity and intrametropolitan travelers from the CAP and city vertiports. The CAP is a combination and an extension of the hub, mode mixer, and Wayport concepts. The CAP is an integrated part of the system which meets the travel demands in the corridor, and interfaces with interstate and international travel.

Source record↗
NASA NTRS1972

Transportation Systems Evaluation

A methodology for the analysis of transportation systems consisting of five major interacting elements is reported. The analysis begins with the causes of travel demand: geographic, economic, and demographic characteristics as well as attitudes toward travel. Through the analysis, the interaction of these factors with the physical and economic characteristics of the transportation system is determined. The result is an evaluation of the system from the point of view of both passenger and operator. The methodology is applicable to the intraurban transit systems as well as major airlines. Applications of the technique to analysis of a PRT system and a study of intraurban air travel are given. In the discussion several unique models or techniques are mentioned: i.e., passenger preference modeling, an integrated intraurban transit model, and a series of models to perform airline analysis.

Fanning, M. L.↗
NASA NTRS1973

Studies in short haul air transportation in the California corridor: Effects of design runway length; community acceptance; impact of return on investment and fuel cost increases, volume 1

The impact of design runway length on the economics and traffic demand of a 1985 short haul air transportation system in the California Corridor was investigated. The community acceptance of new commercial airports for short haul service was studied. The following subjects were analyzed: (1) travel demand, (2) vehicle technology, (3) infrastructure, (4) systems analysis, and (5) effects on the community. The operation of the short haul system is compared with conventional airline operations.

Shevell, R. S.↗
NASA NTRS1973

Forecasting the demand potential for STOL air transportation

A process for predicting the potential demand for STOL aircraft was investigated to provide a conceptual framework, and an analytical methodology for estimating the STOL air transportation market. It was found that: (1) schedule frequency has the strongest effect on the traveler's choice among available routes, (2) work related business constitutes approximately 50% of total travel volume, and (3) air travel demand follows economic trends.

Fan, S.↗
NASA NTRS2012

Metroplex Optimization Model Expansion and Analysis: The Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM)

This report describes the Airline Fleet, Route, and Schedule Optimization Model (AFRS-OM) that is designed to provide insights into airline decision-making with regards to markets served, schedule of flights on these markets, the type of aircraft assigned to each scheduled flight, load factors, airfares, and airline profits. The main inputs to the model are hedged fuel prices, airport capacity limits, and candidate markets. Embedded in the model are aircraft performance and associated cost factors, and willingness-to-pay (i.e. demand vs. airfare curves). Case studies demonstrate the application of the model for analysis of the effects of increased capacity and changes in operating costs (e.g. fuel prices). Although there are differences between airports (due to differences in the magnitude of travel demand and sensitivity to airfare), the system is more sensitive to changes in fuel prices than capacity. Further, the benefits of modernization in the form of increased capacity could be undermined by increases in hedged fuel prices

Sherry, Lance↗
NASA NTRS1999

The Integrated Airport Competition Model, 1998

This paper addresses recent model development by the Directorate General of Civil Aviation (DGCA) and Hague Consulting Group (HCG) concerning long-distance travel. Long-distance travel demand is growing very quickly and raising a great deal of economic and policy issues. There is increasing competition among the main Western European airports, and smaller, regional airports are fighting for market share. New modes of transport, such as high speed rail, are also coming into the picture and affect the mode split for medium distance transport within Europe. Developments such as these are demanding the attention of policy makers and a tool is required for their analysis. For DGCA, Hague Consulting Group has developed a model system to provide answers to the policy questions posed by these expected trends, and to identify areas where policy makers can influence the traveller choices. The development of this model system, the Integrated Airport Competition Model/integraal Luchthaven Competitie Model (ILCM), began in 1992. Since that time the sub-models, input data and user interface have been expanded, updated and improved. HCG and DGCA have transformed the ILCM from a prototype into an operational forecasting tool.

Veldhuis, J.↗
NASA NTRS1999

The Integrated Airport Competition Model, 1998

This paper addresses recent model development by the Directorate General of Civil Aviation (DGCA) and Hague Consulting Group (HCG) concerning long-distance travel, Long-distance travel demand is growing very quickly and raising a great deal of economic and policy issues. There is increasing competition among the main Western European airports, and smaller, regional airports are fighting for market share. New modes of transport, such as high speed rail, arc also coming into the picture and affect the mode split for medium distance transport within Europe. Developments such as these are demanding the attention of policy makers and a tool is required for their analysis. For DGCA, Hague Consulting Group has developed a model system to provide answers to the policy questions posed by these expected trends, and to identify areas where policy makers can influence the traveller choices. The development of this model system, the Integrated Airport Competition Model/Integral Luchthaven Competitive Model (ILCM), began in 1992. Since that time the sub-models, input data and user interface have been expanded, updated and improved. HCG and DGCA have transformed the ILCM from a prototype into an operational forecasting tool.

Veldhuis, J.↗