Presentation 2005-12-13
Proposal of auto-learning following fuzzy model vehicle with extrapolation for microscopic road traffic simulation
Takashi HORIKOSHI, Naoaki ITAKURA, Nakaji HONDA,
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Abstract(in English) In our previous study for the development of the microscopic road traffic simulator(MITRAM), we proposed a fuzzy model for vehicle(FMV) and an auto-learning following FMV(AF-FMV) that can simulate a following vehicle with using neural networks. It was confirmed that the AF-FMV could exactly simulate the following vehicle within the input parameter domain. On the other hand, the AF-FMV could not out of the input parameter domain. This domain was determined and limited by learning measurement data so that the AF-FMV could not be always used in various situations. In this study, we proposed the AF-FMV that has ability to extrapolate out of the domain. It was found the AF-FMV in this study cold simulate more exactly than the AF-FMV in our previous study.
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Keyword(in English) Modeling / Simulation / Fuzzy / Neural Network
Paper # ITS2005-39
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Committee ITS
Conference Date 2005/12/6(1days)
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Registration To Intelligent Transport Systems Technology (ITS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Proposal of auto-learning following fuzzy model vehicle with extrapolation for microscopic road traffic simulation
Sub Title (in English)
Keyword(1) Modeling
Keyword(2) Simulation
Keyword(3) Fuzzy
Keyword(4) Neural Network
1st Author's Name Takashi HORIKOSHI
1st Author's Affiliation Department of Systems Engineering, The University of Electro-Communications()
2nd Author's Name Naoaki ITAKURA
2nd Author's Affiliation Department of Systems Engineering, The University of Electro-Communications
3rd Author's Name Nakaji HONDA
3rd Author's Affiliation Department of Systems Engineering, The University of Electro-Communications
Date 2005-12-13
Paper # ITS2005-39
Volume (vol) vol.105
Number (no) 464
Page pp.pp.-
#Pages 6
Date of Issue