Spatial interaction model for trip-chaining behavior based on entropy maximizing method

In this paper, we propose a new spatial interaction model for trip-chaining behavior that consists of a sequence of movements. Particularly, including the origin-destination constraints, we generalize the traditional entropy maximizing model to deal with trip-chaining behaviors. Traditional entropy models should be noted in terms of a theoretical derivation of the gravity model and its validity to real data. However, these models only deal with simple movements from origin to destination. On the contrary, people frequently visit several destinations in one trip and make a sequence of movements. In this regard of view, we extend the traditional entropy model, and propose a general framework for deriving trip-chain distributions incorporating a sequence of movements. This model enables us to estimate the trip-chain distribution to maximize the entropy under several constraints. Finally, we apply the model to a person trip survey in the Tokyo metropolitan area to examine the validity of the model.