Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 3.77 MB
Add to list
  1. Search results
  2. Opportunistic in-vehicle noise measur...

Opportunistic in-vehicle noise measurements assess road surface quality to improve noise mapping : preliminary results from the MobiSense project

Luc Dekoninck (UGent) , Wout Van Hauwermeiren (UGent) , Joachim David, Karlo Filipan, Toon De Pessemier (UGent) , Bert De Coensel (UGent) , Wout Joseph (UGent) , Luc Martens (UGent) and Dick Botteldooren (UGent)
(2019) Proceedings of the 23rd International Congress on Acoustics : integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany. p.7971-7977
Author
Organization
Abstract
The quality of road pavements affects noise emission caused by tire-road interactions. This in turn affects the health and well-being of residents near these roads. Road pavement quality degrades over time due to wear, accidents, and infrastructure works. These local features are usually not included in noise mapping due to the lack of high-quality information on pavements with enough spatial resolution.The aim of Mobisense is to assess the quality of the road surface by performing opportunistic noise and vibration measurements inside vehicles that are on the road for other purposes than road quality measurement. In the demonstrator phase of the project, 20 vehicles collect data while the drivers make their usual trips. Measurements from all vehicles are combined using machine learning techniques. This removes engine noise, corrects for vehicle specific speed dependence, and finally determines a rolling noise proxy in third-octave bands. This rolling noise correction includes the effect of pavement type as well as the effect of road surface degradation. This local variation in road surface quality is included as a correction in the rolling noise component of CNOSSOS and used to calculate a subset of the noise map for the Flemish region in Belgium. Including road surface quality in this way changes noise maps locally over a range of 6 dBA.
Keywords
noise mapping, road surface, big data

Downloads

  • Download
    ACOUST 505.pdf
    • full text (Published version)
    • |
    • open access
    • |
    • PDF
    • |
    • 3.77 MB

Citation

Please use this url to cite or link to this publication:

MLA
Dekoninck, Luc, et al. “Opportunistic In-Vehicle Noise Measurements Assess Road Surface Quality to Improve Noise Mapping : Preliminary Results from the MobiSense Project.” Proceedings of the 23rd International Congress on Acoustics : Integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany, edited by Martin Ochmann et al., Deutsche Gesellschaft für Akustik, 2019, pp. 7971–77, doi:10.18154/RWTH-CONV-239365.
APA
Dekoninck, L., Van Hauwermeiren, W., David, J., Filipan, K., De Pessemier, T., De Coensel, B., … Botteldooren, D. (2019). Opportunistic in-vehicle noise measurements assess road surface quality to improve noise mapping : preliminary results from the MobiSense project. In M. Ochmann, M. Vorländer, & J. Fels (Eds.), Proceedings of the 23rd International Congress on Acoustics : integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany (pp. 7971–7977). https://doi.org/10.18154/RWTH-CONV-239365
Chicago author-date
Dekoninck, Luc, Wout Van Hauwermeiren, Joachim David, Karlo Filipan, Toon De Pessemier, Bert De Coensel, Wout Joseph, Luc Martens, and Dick Botteldooren. 2019. “Opportunistic In-Vehicle Noise Measurements Assess Road Surface Quality to Improve Noise Mapping : Preliminary Results from the MobiSense Project.” In Proceedings of the 23rd International Congress on Acoustics : Integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany, edited by Martin Ochmann, Michael Vorländer, and Janina Fels, 7971–77. Deutsche Gesellschaft für Akustik. https://doi.org/10.18154/RWTH-CONV-239365.
Chicago author-date (all authors)
Dekoninck, Luc, Wout Van Hauwermeiren, Joachim David, Karlo Filipan, Toon De Pessemier, Bert De Coensel, Wout Joseph, Luc Martens, and Dick Botteldooren. 2019. “Opportunistic In-Vehicle Noise Measurements Assess Road Surface Quality to Improve Noise Mapping : Preliminary Results from the MobiSense Project.” In Proceedings of the 23rd International Congress on Acoustics : Integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany, ed by. Martin Ochmann, Michael Vorländer, and Janina Fels, 7971–7977. Deutsche Gesellschaft für Akustik. doi:10.18154/RWTH-CONV-239365.
Vancouver
1.
Dekoninck L, Van Hauwermeiren W, David J, Filipan K, De Pessemier T, De Coensel B, et al. Opportunistic in-vehicle noise measurements assess road surface quality to improve noise mapping : preliminary results from the MobiSense project. In: Ochmann M, Vorländer M, Fels J, editors. Proceedings of the 23rd International Congress on Acoustics : integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany. Deutsche Gesellschaft für Akustik; 2019. p. 7971–7.
IEEE
[1]
L. Dekoninck et al., “Opportunistic in-vehicle noise measurements assess road surface quality to improve noise mapping : preliminary results from the MobiSense project,” in Proceedings of the 23rd International Congress on Acoustics : integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany, Aachen, Germany, 2019, pp. 7971–7977.
@inproceedings{8630701,
  abstract     = {{The quality of road pavements affects noise emission caused by tire-road interactions. This in turn affects the health and well-being of residents near these roads. Road pavement quality degrades over time due to wear, accidents, and infrastructure works. These local features are usually not included in noise mapping due to the lack of high-quality information on pavements with enough spatial resolution.The aim of Mobisense is to assess the quality of the road surface by performing opportunistic noise and vibration measurements inside vehicles that are on the road for other purposes than road quality measurement. In the demonstrator phase of the project, 20 vehicles collect data while the drivers make their usual trips. Measurements from all vehicles are combined using machine learning techniques. This removes engine noise, corrects for vehicle specific speed dependence, and finally determines a rolling noise proxy in third-octave bands. This rolling noise correction includes the effect of pavement type as well as the effect of road surface degradation.  This  local  variation  in  road  surface  quality  is  included  as  a  correction  in  the  rolling  noise component of CNOSSOS and used to calculate a subset of the noise map for the Flemish region in Belgium. Including road surface quality in this way changes noise maps locally over a range of 6 dBA.}},
  author       = {{Dekoninck, Luc and Van Hauwermeiren, Wout and David, Joachim and Filipan, Karlo and De Pessemier, Toon and De Coensel, Bert and Joseph, Wout and Martens, Luc and Botteldooren, Dick}},
  booktitle    = {{Proceedings of the 23rd International Congress on Acoustics : integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany}},
  editor       = {{Ochmann, Martin and Vorländer, Michael and Fels, Janina}},
  isbn         = {{9783939296157}},
  issn         = {{2226-7808}},
  keywords     = {{noise mapping,road surface,big data}},
  language     = {{eng}},
  location     = {{Aachen, Germany}},
  pages        = {{7971--7977}},
  publisher    = {{Deutsche Gesellschaft für Akustik}},
  title        = {{Opportunistic in-vehicle noise measurements assess road surface quality to improve noise mapping : preliminary results from the MobiSense project}},
  url          = {{http://dx.doi.org/10.18154/RWTH-CONV-239365}},
  year         = {{2019}},
}
Altmetric
View in Altmetric