A causal discovery approach to study key mixed traffic-related factors and age of highway affecting raveling

The link between traffic loads and pavement distress remains uncertain. In this paper, the authors offer a new way to investigate causal relations between mixed traffic and pavement raveling. The method incorporates causal discovery, and is applied to five porous asphalt highways in the Netherlands with large data sets. The authors’ findings show an indirect connection between traffic volume and raveling, with a road's age as a factor. In addition, the results indicate that the extent to which vehicle types contribute to raveling varies with highway and lane geometrics. Further work on causal discovery models is needed because of confusing correlations among traffic variables. While the authors’ study does not conclusively show that traffic contributes to pavement raveling, there is sufficient evidence against rejecting the idea.

• Record URL:
  • https://doi.org/10.1111/mice.13222
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/10939687
• Supplemental Notes:
  • © 2024 The Authors. Computer-Aided Civil and Infrastructure Engineering published by Wiley Periodicals LLC on behalf of Editor
• Authors:
  • Wang, Zili
  • Krishnakumari, Panchamy
  • Anupam, Kumar
  • van Lint, Hans
  • Erkens, Sandra
• Publication Date: 2024-10-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 2861-2880
• Serial:
  • Computer-Aided Civil and Infrastructure Engineering
  • Volume: 39
  • Issue Number: 19
  • Publisher: Blackwell Publishing
  • ISSN: 1093-9687
  • Serial URL: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1467-8667

Subject/Index Terms

• TRT Terms: Data analysis; Pavement distress; Porous pavements; Traffic data; Traffic loads; Vehicle mix
• Geographic Terms: Netherlands
• Subject Areas: Data and Information Technology; Highways; Maintenance and Preservation; Pavements;

Filing Info

• Accession Number: 01936927
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 15 2024 9:47AM