Opportunistic In-Vehicle Noise Measurements assess Road Surface Quality to Improve Noise Mapping: Preliminary Results from the MobiSense Project.
* Presenting author
The quality of road pavements affects noise emission caused by tire-road interactions. This affects the health and well-being of residents near these roads. The quality of the third-party data to determine the road surface noise classification is poor to not existing. Road pavement quality degrades over time due to wear, accidents, and infrastructure works. These local features are not included in the current noise mapping methodology.The aim is to assess the quality of the road surface by performing opportunistic noise measurements inside vehicles. In the demonstrator phase of the project, 20 vehicles collect data by random sampling. Each vehicle driver performs his own trips and all data is combined in an artificial intelligence implementation. Engine noise is removed, vehicle specific speed corrections are applied and a rolling noise proxy in third-octave bands is determined. The rolling noise provides the road surface quality correction including the degree of local road surface degradation. In the project area, this local road surface quality is included in the rolling noise component for the noise map calculations for Flanders (Belgium).