Entropy Models of Trip Distribution

Abstract

Entropy maximization approach has been widely used in transportation planning. It provides theoretical basis for a class of forecast models on traffic demand. In this paper, the concept of entropy from information theory is borrowed to describe inhabitant trip distribution and then a trip distribution model is presented under constraints of typical characteristics based on origin moments. The model is characteristic of generality. The concrete form of the model depends on the order of the highest origin moment which has a great impact on the precision of the model and the labor of parameters calibration. The paper expatiates on this situation and puts forward an iteration method to ascertain the parameters in the model. And then, an entropy method is given to compare the difference of the models for selection. The application of the models and the methods is illustrated via 2001 trip data from the city of Changchun, China.