Model Predictive Control of Traffic Flow Based on Hybrid System Modeling(Systems and Control)
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概要
- 論文の詳細を見る
This paper presents a new framework for traffic flow control based on an integrated model description by means of Hybrid Dynamical System (HDS). The geometrical information on the traffic network is characterized by Hybrid Petri Net (HPN). Then, the algebraic behavior of traffic flow is transformed into Mixed Logical Dynamical Systems (MLDS) form in order to introduce an optimization technique. These expressions involve both continuous evolution of traffic flow and event driven behavior of traffic signal. HPN allows us to easily formulate the problem for complicated and large-scale traffic network due to its graphical understanding. MLDS enables us to optimize the control policy for traffic signal by means of its algebraic manipulability and use of model predictive control framework. Since the behavior represented by HPN can be directly transformed into corresponding MLDS form, the seamless incorporation of two different modeling schemes provide a systematic design scenario for traffic flow control.
- 社団法人電子情報通信学会の論文
- 2005-02-01
著者
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Kim Young
Nagoya University
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Okuma Shigeru
Nagoya Univ. Aichi Jpn
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Okuma Shigeru
Nagoya University
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SUZUKI Tatsuya
Nagoya University
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SUZUKI TATSUYA
Graduate School of Engineering, Nagoya University
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KATO Tatsuya
Nagoya University
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KIM YoungWoo
Nagoya University
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Kim Youngwoo
Graduate School Of Electrical Engineering Nagoya University
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Suzuki Tatsuya
Department Of Mechanical Science And Engineering Graduate School Of Engineering Nagoya University
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Kato T
Nagoya University
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