Abstract
The detection of approaching vehicles is a very important topic on the development of complementary traffic safety systems. However, the majority of the proposed approaches are very complex and not suitable for embedded applications. This paper proposes a new sound approaching detection algorithm specifically intended for hardware implementation. Experimental results show higher accuracy and earlier detection when comparing to other methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Fausett, L.: Neural Networks Based on Competition. In: Fundamentals of Neural Networks: architectures, algorithms and applications, Fundamentals of Neural Networks, 1st edn., New Jersey, pp. 156–217 (1994)
Gupte, S., Masoud, O., Martin, R.F.K., Papanikolopoulos, N.P.: Detection and classification of vehicles. IEEE Transactions on Intelligent Transportation Systems 3(1), 37–47 (2002)
Hoshino, H.: Approaching vehicles detection system by using vehicle noise for driver support. Journal of the Acoustical Society of Japan 62(3), 265–274 (2006)
Kodera, K., Itai, A., Yasukawa, H.: Estimation of speed and arrival time of approaching vehicles using sound. IEICE Technical Report, 13–18 (2007)
Kugler, M., Benso, V.A.P., Kuroyanagi, S., Iwata, A.: A novel approach for hardware based sound classification. In: Köppen, M., Kasabov, N., Coghill, G. (eds.) ICONIP 2008. LNCS, vol. 5507, pp. 859–866. Springer, Heidelberg (2009)
Kugler, M., Iwasa, K., Benso, V.A.P., Kuroyanagi, S., Iwata, A.: A complete hardware implementation of an integrated sound localization and classification system based on spiking neural networks. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds.) ICONIP 2007, Part II. LNCS, vol. 4985, pp. 577–587. Springer, Heidelberg (2008)
Kuroyanagi, S., Iwata, A.: Auditory pulse neural network model to extract the inter-aural time and level difference for sound localization. IEICE Transactions on Information and Systems 77(4), 466–474 (1994)
Pickles, J.O.: An Intruduction to the Physiology of Hearing, 2nd edn. Academic Press, London (1988)
Wang, C.C., Thorpe, C.E., Thrun, S.: Online simultaneous localization and mapping with detection and tracking of moving objects: theory and results from a ground vehicle in crowded urban areas. In: ICRA, pp. 842–849. IEEE, Los Alamitos (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tsuzuki, H., Kugler, M., Kuroyanagi, S., Iwata, A. (2010). A Novel Approach for Sound Approaching Detection. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Models and Applications. ICONIP 2010. Lecture Notes in Computer Science, vol 6444. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17534-3_50
Download citation
DOI: https://doi.org/10.1007/978-3-642-17534-3_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17533-6
Online ISBN: 978-3-642-17534-3
eBook Packages: Computer ScienceComputer Science (R0)