Abstract
Vehicle classification is now an important part of Intelligent Transportation Systems (ITS). Especially in toll station and parking, real-time vehicle classification technology is used to determine the vehicle information. A novel method based on frequency domain energy spectrum of geomagnetic sensor for real-time vehicle classification was proposed in this paper. According to the definitions of eight frequency domain energy formulations, the energy values with different frequency regions could by computed. Compared with those energy values, the optimal frequency region and energy formulation were obtained. As each vehicle classification has a specific energy region, the classification of each vehicle can be easily differentiated by its energy value. Results show that the vehicle classification method proposed in this paper has an excellent performance and the average accuracy is more than 90 %. Besides, the algorithm makes it easier for applications in sensor nodes with limited computational capability and energy source.
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Acknowledgments
This work is supported by the National Natural Science Foundation of China (61104164) and the Fundamental Research Funds for the Central Universities (2012YJS059), and is also supported by the National 863 Program of China (2012AA112401).
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Zhang, P., Li, H., Dong, H., Jia, L., Jin, M. (2013). Real-Time Vehicle Classification Based on Frequency Domain Energy Spectrum. In: Sun, Z., Deng, Z. (eds) Proceedings of 2013 Chinese Intelligent Automation Conference. Lecture Notes in Electrical Engineering, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38466-0_60
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DOI: https://doi.org/10.1007/978-3-642-38466-0_60
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