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 ABSTRACT

Most trip generation analysis procedures utilized in transport planning studies are based on either zonal regression or cross-classification analysis. There has been continuous criticisms of the quality of these techniques for a variety of reasons. The use of the Generalized Linear Model (GLM) framework in conducting household-level trip generation analysis has been the subject of some research, but has not been fully explored, and only a few applications have been reported. There are several advantages that the GLM approach can provide, including the variety of the statistical models that can be investigated and tested within the general framework, the consistency in the selection of the explanatory variables, and in the way low-frequency observations are handled.

This paper outlines briefly the generalized linear model framework and describes the  statistical model options it provides for the household-level trip generation analysis,  include regression, ANOVA and analysis of covariance models with various link functions and assumptions about the underlying distribution of trip observations in the cells. Data on work trips and household characteristics from Kuwait generated from an extensive home interview survey is utilized to demonstrate the practical nature of proposed framework and the possibilities it offers. The application uses data of Kuwaiti in three housing types. Work trips are found to be influenced by car ownership the number of adults and children in the household. Some of the interaction effects are found to be significant.