Optimal Sampling Strategy for Acceptance Decision in Highway Construction: a Cost–Benefit Analysis Approach

State Departments of Transportation (DOTs) make acceptance and pay factor decisions regarding pavement based on testing results of random samples. Two critical questions in practice are: (1) how many samples should be acquired for testing to ensure the reliability of acceptance and pay factor decisions, and (2) how to motivate contractors to share the acceptance testing cost to address the resource shortage at state DOTs? Answering these two questions is important, as it will provide guidance for state DOTs to reshape their current sampling and testing paradigms to achieve more reliable acceptance and pay factor decisions. This paper presents a cost-benefit analysis approach from the perspectives of both agency and contractor. It first assesses the sampling variability in the tested material properties by considering the product intrinsic variance, measurement error, and spatial sampling error. Second, the expected losses of both agency and contractor under various scenarios are computed. Finally, the optimal sampling strategies and the corresponding testing cost sharing plan are derived based on the trade-offs between sampling costs and benefits acquired by both parties. The proposed method is illustrated using Indiana Department of Transportation (INDOT) specification on acceptance and pay factor for the flexural strength tests of Portland cement concrete pavement (PCCP).

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AFH20 Standing Committee on Quality Assurance Management.
  • Authors:
    • Cai, Jiannan
    • Li, Shuai
    • Gao, Qingyi
    • Chun, Hyonho
    • Nantung, Tommy
    • Cai, Hubo
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References;
  • Pagination: 7p

Subject/Index Terms

Filing Info

  • Accession Number: 01658697
  • Record Type: Publication
  • Report/Paper Numbers: 18-00218
  • Files: TRIS, TRB, ATRI
  • Created Date: Jan 31 2018 5:00PM