講演抄録/キーワード |
講演名 |
2009-01-30 10:10
自動車のタイヤ騒音を用いた路面状況の自動検出 ○ワッティワット コングラッタナプラサート・野村英之・鎌倉友男(電通大)・上田浩次(名古屋電機工業) EA2008-125 |
抄録 |
(和) |
(まだ登録されていません) |
(英) |
This paper proposes a new method for automatically detecting the states of the road surface from tire noises of vehicles. The methods are based on a Fast Fourier Transform analysis, an artificial neural network, and the mathematical theory of evidence. The proposed classification is carried out in sets of multiple neural networks using the learning vector quantization networks. The outcomes of the networks are then integrated using the voting decision making scheme. It seems then feasible to detect passively and readily the states of the surface: i.e., as a rule of thumb, dry, wet, snowy and slushy state, automatically. Preliminary classification results for an independent validation set yielded 81.6% correct classification. This was improved to 91% by addition of information about the early state in a final decision. |
キーワード |
(和) |
/ / / / / / / |
(英) |
Road surface conditions / Automobile tire sounds / Frequency analysis / Artificial neural network / Intelligent transportation system / / / |
文献情報 |
信学技報, vol. 108, no. 411, EA2008-125, pp. 55-60, 2009年1月. |
資料番号 |
EA2008-125 |
発行日 |
2009-01-22 (EA) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します.(許諾番号:10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
PDFダウンロード |
EA2008-125 |
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