http://swrc.ontoware.org/ontology#Article
経路選択行動のday-to-dayダイナミクスと交通ネットワーク均衡の形成プロセス
ja
Bayesian learning
day-to-day dynamics
stability of Wardrop equilibrium
中山 晶一朗
金沢大学理工研究域環境デザイン学系
土木学会論文集D
65
1
1-11
2009-01-01
0289-7806
AA12131726
10.2208/jscejd.65.1
Japan Society of Civil Engineers = 土木学会
In this study, we assume that each driver under day-to-day dynamic transportation circumstances chooses a route based on Bayesian learning, and develop a day-to-day dynamical model of network flow. It is found in this model that the driver with Bayesian learning chooses the route which has the minimum travel time the most frequently. Furthermore, we find that an equilibrium point of the day-to-day dynamical model is identical to the Wardrop's equilibrium, and the Wardrop's equilibrium is globally asymptotically stable if initial recognition among drivers is dispersed widely, and the day-to-day dynamical system always converges to the Wordrop's equilibrium.
Copyright (c) 2009 by Japan Society of Civil Engineers
http://www.jstage.jst.go.jp/article/jscejd/65/1/65_1/_article