Processing Variable Forms for Travel Estimation

by Jason C. Yu, (M.ASCE), Prof.; Dept. of Civ. Engrg. and Dir. of Transportation Research Center, Univ. of Utah, Salt Lake City, Utah,
Robert J. Popper, Asst. Prof.; Dept. of Civ. Engrg., Virginia Polytechnic Inst. and State Univ., Blacksburg, Va,

Serial Information: Transportation Engineering Journal of ASCE, 1976, Vol. 102, Issue 1, Pg. 91-104

Document Type: Journal Paper


As applied to intercity travel demand estimation, the conventional gravity model consists of some pairing-like variables which attempt to express certain interactions affecting the travel potential between two cities. This paper explores alternative functional forms of the pairing-like variables, in order to produce a more effective travel demand forecast relationship. The study suggests the use of three statistical procedures for formulating the demand model, based on functional forms of variables that most significantly express the travel demand relationship. The best functional form of the pairing-like variable is defined as the one which will yield a statistically sound model of travel estimation, as indicated by stepwise multiple regression techniques. It is anticipated that by incorporating these variable forms, the predictive power of resulting travel demand models will be substantially improved, while data requirements are minimized.

Subject Headings: Travel demand | Interurban travel | Forecasting | Regression analysis

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