Study Of Route Choice Model Based On Prospect Theory

In the traffic system, there are lots of travelers, who judge the road situations and make decisions as well as choose a reasonable better travel path according to available information and continuous individual experience, in the course of travelling from one place to another. Therefore some researches showed that, travel choice behavior under the uncertainty of traffic system, especially the starting time and the choice of the path in travel behavior, is in line with the basic point of prospect theory. It illuminated that prospect theory can be used in the study of travelers'travel choice decision behavior under real-time information environment.In this paper, it firstly introduces route choice model under the conditions of uncertainty, which theoretically based on including the expected utility theory and random utility theory, prospect theory, artificial neural networks and fuzzy set theory as well as the learning model. By analysis of model has been proposed, it suggested the applicability of prospect theory-based path choice behavior modelling. Then, it put forward the theoretical background as well as theoretical core of the Prospect Theory, and focus on an analysis for the theoretical study status of Prospect Theory and its existing research of combination with the route choice model.Beginning from the traditional route choice reference point based on Prospect Theory, it determined its value function based on the improved time budget based reference point by combined with the time budget and valid path theory as well as its related theory. With setting the travelers'subjective probability as well as weighting function, it proposed a prospect value calculating model of all alternative paths. And then it got the final choice of route choice. Subsequently, by building a road network and setting the network properties and model parameters, a numerical example is constructed. It analyzed different route choices of different travelers under varied traffic conditions, and also did stochastic user equilibrium flow distribution on the network. Finally, though a simple example, it analyzed concretely the different route choice results of travelers differently based on the traditional expected utility-based route choice model, traditional prospect theory-based route choice model as well as the improved prospect theory-based route choice model, and showed that the improved route choice model is better than the original one in illustrating the actual travelers'travel behavior.