SPATIAL INTERACTION MODEL FOR TRIP-CHAINING BEHAVIOR WITH A FOCUS ON CALCULATION EFFICIENCY

Abstract

This paper provides a general framework for a spatial interaction model from the viewpoint of comprising several trips. To estimate the traffic volume distribution of trip-chains, we proposed a new spatial interaction model based on the entropy maximizing model in 2010. In this paper firstly, an efficient calculation method, based on the spatial interaction model, for the proposed trip-chain is discussed. Furthermore, through these mathematical developments, the mathematical relationships between the entropy model, Markov model, and the discrete choice model, which produce the same traffic volume distribution of trip-chains, are clarified. These discussions not only support the entropy model proposed in a previous paper by human sciences based on expected-utility theory but also cover the shortcomings of the existing Markov model and the discrete choice model. It is often pointed out that the Markov model is a pure stochastic model and there is no support from the individual behavior principle. Moreover, the discrete choice model has the problem that the alternative set becomes huge as a result of dealing with trip-chaining behavior, which has a high degree of freedom. We show, under certain assumptions, the Markov model with individual behavior principle and the discrete choice model without enumerating the alternative set. In addition, we clarify the characteristics between the sequential decision making (Markov model) and the simultaneous decision making (discrete choice model) in terms of trip-chaining behavior.