Processing Acoustic Data with Siamese Neural Networks for Enhanced Road Roughness Classification

In recent years, a lot of effort has been put in vehicle safety systems for manned and unmanned driving. Road conditions are crucial among the factors that influence the choice of the driving style and the safety systems. A few works based the detection of the road condition on acoustic sensors mounted on the vehicle using deep learning techniques. In this work we enhance the state of the art by introducing a Siamese Convolutional Neural Network architecture able to achieve improved results for the classification of the road surface roughness. A new dataset is recorded and the approach is tested, achieving a best overall F1-score of 95.6%, improving by 14% the results of the previous method.