Traffic inputs for pavement ME design using Oklahoma data

Mechanistic-empirical pavement design guide (MEPDG) or Pavement ME Design requires traffic inputs in three levels based on the availability of data and the importance of the project. The availability of site-specific (Level 1) traffic data is generally limited due to expensive cost and the accuracy of Level 3 average is unsatisfactory, and therefore the intermedium level (Level 2) traffic data need to be developed. Using multiple years of weigh-in-motion (WIM) and vehicle classification data from Oklahoma, this paper starts with a comprehensive check of the traffic data quality, and generates site-specific traffic inputs that are required in Pavement ME Design. Cluster analysis is then applied to develop homogeneous groups for each traffic input. Subsequently, decision tree model and multinomial regression model are developed for the selection of appropriate traffic clusters under given site design conditions. In addition, a case study is included to evaluate the variations of pavement performance at various levels of traffic inputs.

• Record URL:
  • https://doi.org/10.1007/s42947-019-0020-5
• Record URL:
  • https://link.springer.com/article/10.1007/s42947-019-0020-5
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19966814
• Supplemental Notes:
  • © Chinese Society of Pavement Engineering. Production and hosting by Springer Nature 2019.
• Authors:
  • Li, Qiang Joshua
  • Minnekanti, Srinivas Prudhvi
  • Yang, Guangwei
  • Wang, Chaohui
• Publication Date: 2019-3

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 154-160
• Serial:
  • International Journal of Pavement Research and Technology
  • Volume: 12
  • Issue Number: 2
  • Publisher: Chinese Society of Pavement Engineering
  • ISSN: 1996-6814
  • EISSN: 1997-1400
  • Serial URL: http://www.ijprt.org.tw/index.php
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Case studies; Cluster analysis; Data quality; Decision trees; Mechanistic-empirical pavement design; Pavement performance; Traffic data
• Identifier Terms: Mechanistic-Empirical Pavement Design Guide
• Uncontrolled Terms: Multinomial regression analysis
• Geographic Terms: Oklahoma
• Subject Areas: Design; Highways; Pavements;

Filing Info

• Accession Number: 01713758
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 14 2019 2:31PM