<div class="csl-bib-body">
<div class="csl-entry">Borchers, J.-H., & Sotto, L. F. P. D. (2025). Transverse evenness prediction in asphalt pavement using an artificial neural network. In L. Eberhardsteiner, B. Hofko, & R. Blab (Eds.), <i>Advances in Materials and Pavement Performance Prediction IV : Contributions to the 4th International Conference on Advances in Materials and Pavement Performance Prediction (AM3P 2025), 7-9 May 2025, Vienna, Austria</i> (pp. 543–546). TU Wien, E230-03 Road Engineering. https://doi.org/10.34726/10560</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/218936
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dc.identifier.uri
https://doi.org/10.34726/10560
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dc.description.abstract
A pivotal aspect of pavement management systems (PMS) and road asset management is the deployment of predictive algorithms for pavement performance. The objective of this paper is to investigate the potential of artificial intelligence (AI) in this process, specifically for predicting transverse evenness, which is represented by rut depth and water depth. Firstly, the condition survey and assessment in Germany is described. Then an overview of the current methodology for prediction of road condition data and the artifi- cial neural network (ANN) employed in this paper is given. Subsequently, both methods are evaluated on a subnetwork and their performances are compared, with the employed ANN showing an improved prediction performance.
en
dc.language.iso
en
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dc.relation.ispartofseries
Advances in Materials and Pavements Performance Prediction
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dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
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dc.subject
pavement management system (PMS)
en
dc.subject
pavement performance prediction
en
dc.subject
asphalt pavement
en
dc.subject
rutting
en
dc.subject
artificial neural network (ANN)
en
dc.title
Transverse evenness prediction in asphalt pavement using an artificial neural network
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.identifier.doi
10.34726/10560
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dc.contributor.affiliation
Bundesanstalt für Straßenwesen, Germany
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dc.contributor.affiliation
Technische Universität Braunschweig, Germany
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dc.relation.isbn
978-3-901912-99-3
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dc.relation.doi
10.34726/9259
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dc.description.startpage
543
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dc.description.endpage
546
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dc.rights.holder
TU Wien, E230-03 Road Engineering
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Advances in Materials and Pavement Performance Prediction IV : Contributions to the 4th International Conference on Advances in Materials and Pavement Performance Prediction (AM3P 2025), 7-9 May 2025, Vienna, Austria
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tuw.container.volume
IV
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tuw.peerreviewed
true
-
tuw.book.ispartofseries
Advances in Materials and Pavements Performance Prediction
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tuw.relation.publisher
TU Wien, E230-03 Road Engineering
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tuw.relation.publisherplace
Wien
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tuw.researchTopic.id
C6
-
tuw.researchTopic.id
M8
-
tuw.researchTopic.id
C3
-
tuw.researchTopic.name
Modeling and Simulation
-
tuw.researchTopic.name
Structure-Property Relationsship
-
tuw.researchTopic.name
Computational System Design
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tuw.researchTopic.value
35
-
tuw.researchTopic.value
30
-
tuw.researchTopic.value
35
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tuw.publication.orgunit
E000 - Technische Universität Wien
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dc.identifier.libraryid
AC17636726
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dc.description.numberOfPages
4
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tuw.author.orcid
0000-0001-7037-5826
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dc.rights.identifier
CC BY 4.0
en
dc.rights.identifier
CC BY 4.0
de
tuw.editor.orcid
0000-0003-2153-9315
-
tuw.editor.orcid
0000-0002-8329-8687
-
tuw.editor.orcid
0000-0003-4101-1964
-
tuw.event.name
Advances in Materials and Pavement Performance Prediction 2025 (AM3P 2025)
