| Issue |
MATEC Web Conf.
Volume 308, 2020
2019 8th International Conference on Transportation and Traffic Engineering (ICTTE 2019)
|
|
|---|---|---|
| Article Number | 05002 | |
| Number of page(s) | 4 | |
| Section | Intelligent Transportation and System Design | |
| DOI | https://doi.org/10.1051/matecconf/202030805002 | |
| Published online | 12 February 2020 | |
Research on Traffic Acoustic Event Detection Algorithm Based on Sparse Autoencoder
1 Research Institute of Highway, Ministry of Transport, Beijing 100088, China
2 School of Communication Engineering, Nanjing Institute of Technology, Jiangsu Nanjing, 211167, China
a Corresponding author: zhangdaqing_925@163.com
Road traffic monitoring is very important for intelligent transportation. The detection of traffic state based on acoustic information is a new research direction. A vehicles acoustic event classification algorithm based on sparse autoencoder is proposed to analysis the traffic state. Firstly, the multidimensional Mel-cepstrum features and energy features are extracted to form a feature vector of 125 features; Secondly, based on the computed features, the five-layers autoencoder is trained. Finally, vehicle audio samples are collected and the trained autoencoder is tested. The experimental results show that detection rate of the traffic acoustic event reaches 94.9%, which is 12.3% higher than that of the traditional Convolutional Neural Networks (CNN) algorithm.
© The Authors, published by EDP Sciences, 2020
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