学習ペースカーによるメタ安定相への遷移の実現

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2013/09/01

タイトル(英語): Transition to Metastable Phase by Learning Pace-Car

著者名: 許　海遅（千葉大学大学院工学研究科都市環境システムコース），荒井　幸代（千葉大学大学院工学研究科都市環境システムコース）

著者名(英語): Haichi Xu (Division of Urban Environment Systems, Graduate School Faculty of Engineering, Chiba University), Sachiyo Arai (Division of Urban Environment Systems, Graduate School Faculty of Engineering, Chiba University)

キーワード: 強化学習，自然渋滞，メタ安定，マルチエージェントシミュレーション　　Reinforcement learning，Phantom Traffic Jam，Metastable Phases，Multiagent simulation

要約(英語): In this paper, we introduce an intelligent pace-car in the traffic flow for the purpose of controlling vehicles that follows a pace-car, and show that it is possible to reduce the phantom traffic jam. Under the situation of phantom traffic jam, the instabilities are observed to grow into traveling waves, which are local peaks of high traffic density, although the average traffic density is still moderate, where the highway is not fully congested. The pace-car manages its velocity to control the following vehicles which are forced to brake when they run into such waves.The management strategy of the velocity is acquired by reinforcement learning. We employ the extended Nagel-Schreckenberg model which make the traffic flow maximum. By introducing the learned pace-car, we successfully achieves a phase transition that shifts traffic flow from congestion phase to metastable phase.First, we explain our proposed extended Nagel-Schreckenberg model, and secondly, it is defined that the situation of congestion as the state space to make pace-car learn by reinforcement learning approach. Third, though pace-car finally realizes the highest traffic flow, we evaluate the traffic loss during the period of pace-car's control. As the result. Finally, through the loss evaluation, we show the effectiveness of our approach to acquire the control strategy of pace-car.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.133 No.9 （2013） 特集：エージェントシミュレーションの最新動向

本誌掲載ページ: 1709-1716 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/133/9/133_1709/_article/-char/ja/