Analysis and Design of Information Dynamics and Information Dissemination To Realize Optimal Management of Transportation

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We have been concerned with the desirable mode of information services to control the behavior of a transportation network system. The difficulty of this problem is that optimal traffic assignment is not always satisfied with minimal travel time of each driver. Consequently, this study is an attempt to ascertain how to reconcile these two conflicting viewpoints. Most previous studies emphasized the driver's decision making processes to resolve this paradox. We specifically examined the information services side to make traffic flow desirable. First, we adopt a reinforcement learning framework to acquire a strategy for solving the paradox. Secondly, we show the criteria of information distribution to realize a desirable traffic flow through some experimentation.