自動車のタイヤ騒音を用いた路面状況の自動検出 Automatic Detection of Road Surface Conditions using Tire Noise from Vehicles
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.
- 電子情報通信学会技術研究報告. EA, 応用音響
電子情報通信学会技術研究報告. EA, 応用音響 108(411), 55-60, 2009-01-22