On-board wet road surface identification using tyre/road noise and Support Vector Machines

In this paper we propose an asphalt status classification system based on real-time acoustic analysis of tyre/road noise. The proposed system uses a practical approach that allows it to be integrated into a real vehicle. We present the system architecture used to measure the noise and the signal processing algorithms used for the classification of the asphalt state. A practical implementation of the proposed system has been developed and tested. For this preliminary prototype, only wet and dry asphalt states have been covered. Obtained wet/dry classification results have been reported, showing very high success rates.