Regression model

In this model an additive functional form is assumed to exist between the factors which affect trip generation and the number of trips generated. Generally, a linear function of the following form is used:

$$T_i = \alpha_1 z_{1,i} + \alpha_2 z_{2,i} + \cdots + \alpha_n z_{n,i}$$ (2)

where, $\alpha_k$ are parameters of the regression function and $z_{k,i}$ is the value of the $k^{th}$ variable (like income, automobile ownership, number of members in a household, etc.) for the $i^{th}$ zone.

As can be seen using this model to determine the number of trips generated by a zone is a simple matter when all the parameters of the regression function are known. Obviously, the parameters are determined by using some parameter estimation technique like Ordinary Least Squares or Maximum Likelihood Technique on empirically obtained data on $z_k$ variables and $T_i$. For a good description of regression analysis and the parameter estimation techniques mentioned here one may refer to any book on introductory statistical methods or basic econometrics; for example, Gujarati [#!guj1!#] and Wonnacot and Wonnacot [#!won1!#].

Discussion: Generally the models of trip generation include variables which reflect the number of potential trip makers and the propensity of potential trip makers to make a trip. However, none of the present models incorporate variables which reflect the accessibility factor. This is possibly the single largest factor as to why trip generation models do not do very well in predicting the number of trips generated.