UBC Theses and Dissertations

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UBC Theses and Dissertations

Criteria for forecasting intercity air travel Oehm, Peter Friedrich

Abstract

Airports, as terminals for air transportation, are places for both the movement of passengers and freight. They have a major influence on urban development. The significance of air transportation is often underestimated by civic officials and transportation planners. Functionally, airports are no different from the older and well established rail or port terminals around which most of our contemporary metropolises have developed. An understanding of the nature of present and future air traffic enables the transportation planner to foresee the urban spatial structure and its general relationship to the intercity transportation network. Before the impact of the airport upon the regional urban structure can be ascertained, it is necessary to establish the position and function of the airport within the regional transportation infrastructure. In order to determine this, it is necessary to know the present and future travel movements emanating from it and terminating there. Herein an hypothesis is postulated to determine the relative significance of a set of selected factors upon Vancouver's intercity air travel and ultimately their influence upon its spatial structure. INTERCITY AIR PASSENGER TRAFFIC IS INFLUENCED BY FOUR MAJOR FACTORS: POPULATION, INTERCITY AIR DISTANCE, INTERCITY LINE TIME, AND INTERCITY LINE PRICE. THIS SET OF INDEPENDENT VARIABLES CAN BE POSTULATED IN A MATHIMATICAL MODEL TO ADEQUATELY DESCRIBE AND FORECAST LEVELS OF INTERCITY AIR PASSENGER TRAFFIC. A description and review of current air traffic forecasting methods is continued out in Chapter II. Five methods are-outlined as follows: the market analysis technique, the national income method, the city analysis approach, the econometric model, and the gravity model technique. The gravity model technique is selected for emphasis in this thesis. Chapter II presents in turn a brief history of the evolution of the gravity model as a traffic predicting device. It is shown that the gravity model is a valid predictive device for forecasting the gross- traffic movements between two traffic centres. Chapter III is devoted to a discussion of the significance of the gravity model to air traffic prediction. As generally conceived, the gravity model relates the influence of urban population and interurban distance to intercity air traffic movements. This traditional theory of gravitational interactance has been modified by a number of air transportation researchers. Multiple regression analysis is the primary method of Investigation in each of these studies. By means of regression analysis, the variables, as selected for inclusion in the hypothesis, have been shown to have validity in some United States cities, Certain major assumptions are set out in order that the selected variables can be isolated and studied in the allotted time period. The limitations imposed upon each of the selected variables are outlined in Chapter IV. In Chapter IV linear regression analysis is used to obtain the relative significance of each variable as an air traffic determinant. The validity for inclusion of a variable as a factor of air traffic generation, is determined by the coefficient of correlation for that variable. The coefficients of correlation for the selected variables ranged from 0.76 to 0.85. This would indicate that the selected variables are valid components of the relationship as postulated in the hypothesis. Chapter V outlines the basic method of research used. The main techniques employed include the gravity model and multiple regression analysis. By this analysis in an iterative manner, several valid relationships have been established between air traffic volume and the selected variables. However, while these relationships are considered to be reasonable, their validity is affected by constraints placed on them in time, in space, and in data as is presented-in Chapters V and VI. Prom these relationships, certain conclusions are postulated. Gravity models are useful in examining the relationship between demographic factors, transport factors, and intercity air passenger traffic. Distance proved to be a variably important factor. It appears to influence air traffic in a definite manner which depends upon the population of the study cities. Distance, according to the research, is less of a restrictive factor for travel involving larger cities as is shown in Table 10. As for intercity travel time, there is no doubt that it is an important factor on some routes. In particular, differences in time resulting from different types of equipment may affect a traveller's decision. The apparent friction effect of time/distance for travel among smaller cities may only reflect the fact that slower aircraft are used to serve these small communities. It is possible that the introduction of short haul jet aircraft will minimize this difference. The regression equation developed here can only be used as a predictive device in certain cases, in particular, on routes connecting large population centres. On many routes, the standard deviations are low, and, thus predictions are reasonably accurate. That is, when annual predicted traffic is within 20 percent of actual annual traffic, it is accepted as a good projection. However, the relationships, as established, leave much of the air traffic variability unexplained. Consequently, areas for further study are suggested in the concluding portion of the thesis. The research areas recommended for further study should include several recent developments in intercity common carrier transportation. These technological achievements include: (l) the development of a better short haul aircraft (ie. D.C. 9 or Boeing 737); (2) the provision of jumbo jets by 1970; (3) the introduction of V.T.O.L. and S.T.O.L. services by 1973; (4) the provision of a commercial supersonic vehicle by 1975; and, (5) the inauguration of high speed passenger train services on routes of 100 to 500 miles in length. In Canada and the United States, the degree of success of these new experimental passenger train services places definite limitations on the validity of predicting short haul air traffic over a long time period.

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