| Summary: | 碩士 === 國立交通大學 === 交通運輸研究所 === 86 === The Gravity-type Interactive Markov models(GIM models) were
introduced by Smith and Hsieh in 1994,in which
migration flows in each time period are postulated to vary
directly with some population-dependent measure of
attractiveness and inversely with some symmetric measure of
migration costs. From the viewpoint of theoretical
analysis, the choice behavior of individuals inGIM models is
similar to that of drivers in selecting routes in logit-based
stochastic traffic assignment problems.
This study is trying to formulate the GIM model of the
stochastic traffic assignment in a road network. The
followings will be the goal of this study: (1). Prove that
the steady-state conditions of the GIM model is equivalent to
the stochastic user equilibrium (SUE) conditions of the
problems.(2).Develop a new algorithm for solving the SUE of
the problems.(3).Compare the GIM algorithm with exiting
algorithm, e.g. Frank-Wolfe method, MSA.(4).Analyze the
convergence to the SUE of the GIM algorithm.
This method has implemented by Mathmatica. The computation of
different algorithms on different examples shows that
the adjustment ratio have a great influence on the speed of
convergence. And the level of overlapping in the network
is slight, we can solve the stochastic user equilibrium problems
that haveoverlapping links in the network by GIM algorithm.
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