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dc.contributor.authorHauwermeiren, WV
dc.contributor.authorDavid, J
dc.contributor.authorDekoninck, L
dc.contributor.authorDe Pessemier, T
dc.contributor.authorJoseph, W
dc.contributor.authorBotteldooren, D
dc.contributor.authorMartens, L
dc.contributor.authorFilipan, K
dc.contributor.authorDe Coensel, B
dc.date.accessioned2020-04-16T00:26:07Z
dc.date.available2020-04-16T00:26:07Z
dc.date.issued2019
dc.identifier.isbn9781999181000
dc.identifier.urihttp://hdl.handle.net/10072/393103
dc.description.abstractThe quality of road pavements influences noise and vibration emissions caused by tire-road interactions. This affects the drivers, passengers and load but also health and well-being of residents near these roads. Road pavement quality degrades over time due to wear, accidents, and infrastructure works. Monitoring road pavement state can rely on dedicated vehicles equipped with a CPX trailer (Close-Proximity method) or with laser texture scanning. However, using this approach, it remains difficult to cover the whole road infrastructure network at regular intervals. In this paper, an opportunistic approach is proposed: equipping cars that are on the road for other purposes with noise and vibration sensors. This way, personnel costs are avoided, and timeliness of the information could be increased. The proposed method collects spectral sound and vibration data from a sensor box placed near the rear wheel of the car. These data are transmitted over 3G to a central server. The box is also equipped with a GPS tracker that allows locating the vehicles on a road map and deriving their driving speed. Data analytics accounts for modifiers such as the driving speed and the transfer function between the tire and the microphone. Features related to the roughness of the pavement are extracted and the abundance of data is used to eliminate confounders such as the engine noise and vibrations, other cars and trucks driving near the sensor box, or music and voices. The resulting texture indicators for each 20-meter road segment correlate very well to CPX and laser texture measurements. The difference between worn-out roads (>15 years) and new pavements (<5 years) is statistically significant
dc.description.peerreviewedYes
dc.publisherInternational Institute of Acoustics and Vibration (IIAV)
dc.publisher.urihttp://icsv26.org/
dc.relation.ispartofconferencename26th International Congress on Sound and Vibration (ICSV26)
dc.relation.ispartofconferencetitleProceedings of the 26th International Congress on Sound and Vibration, ICSV 2019
dc.relation.ispartofdatefrom2019-07-07
dc.relation.ispartofdateto2019-07-11
dc.relation.ispartoflocationMontréal, Canada
dc.subject.fieldofresearchEnvironmental Science and Management
dc.subject.fieldofresearchAcoustics and Noise Control (excl. Architectural Acoustics)
dc.subject.fieldofresearchcode0502
dc.subject.fieldofresearchcode091301
dc.titleAssessing road pavement quality based on opportunistic in-car sound and vibration monitoring
dc.typeConference output
dc.type.descriptionE1 - Conferences
dcterms.bibliographicCitationHauwermeiren, WV; David, J; Dekoninck, L; De Pessemier, T; Joseph, W; Botteldooren, D; Martens, L; Filipan, K; De Coensel, B, Assessing road pavement quality based on opportunistic in-car sound and vibration monitoring, Proceedings of the 26th International Congress on Sound and Vibration, ICSV 2019, 2019
dc.date.updated2020-04-16T00:23:50Z
dc.description.versionPublished
gro.rights.copyright© 2019 Australian Acoustical Society. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
gro.hasfulltextFull Text
gro.griffith.authorDe Coensel, Bert


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