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<p>This study compares expert-based multi-criteria decision analysis (MCDA) with the traditional Pavement Condition Index (PCI) for prioritizing pavement maintenance. Using data on PCI, traffic volume, crashes, costs, and public complaints, along with weights from 35 experts, the research developed different prioritization scenarios. The MCDA approach, using average expert weights, assigned the highest importance to public complaints (PC: 30.7%) and traffic volume (ADT: 17.9%), significantly shifting priorities from the PCI-only method. Sensitivity analysis revealed the ranking framework is robust, with results remaining consistent despite moderate variations in expert judgment. The factors most influential in changing rankings were public complaints (PC), crash data (CR), and maintenance cost (MC). The findings demonstrate that integrating expert judgment with objective data creates more robust and inclusive maintenance plans, providing valuable insights for transportation agencies.</p>

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A comparative analysis of pci-only and multi-criteria priority index methods for pavement maintenance

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月9日

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  • Yara Zayed,
  • Huthaifa I. Ashqar,
  • Amjad Issa

摘要

This study compares expert-based multi-criteria decision analysis (MCDA) with the traditional Pavement Condition Index (PCI) for prioritizing pavement maintenance. Using data on PCI, traffic volume, crashes, costs, and public complaints, along with weights from 35 experts, the research developed different prioritization scenarios. The MCDA approach, using average expert weights, assigned the highest importance to public complaints (PC: 30.7%) and traffic volume (ADT: 17.9%), significantly shifting priorities from the PCI-only method. Sensitivity analysis revealed the ranking framework is robust, with results remaining consistent despite moderate variations in expert judgment. The factors most influential in changing rankings were public complaints (PC), crash data (CR), and maintenance cost (MC). The findings demonstrate that integrating expert judgment with objective data creates more robust and inclusive maintenance plans, providing valuable insights for transportation agencies.