Optimal Preventive Maintenance Timing for Expressway Asphalt Pavements Based on PMS Deterioration Modeling and Life-Cycle Cost Analysis

The preventive maintenance (PM) of asphalt pavements reduces life-cycle costs and minimizes resource consumption compared with reactive rehabilitation, yet its cost-effectiveness is highly sensitive to application timing. This study develops a data-driven framework for determining optimal PM timing on Korean expressways by integrating network-level pavement management system (PMS) deterioration modeling with life-cycle cost analysis (LCCA). Using 10-year PMS time-series data from approximately 2200 asphalt pavement sections (2012–2021), a nonlinear regression of the Highway Pavement Condition Index (HPCI) yielded an exponential deterioration model with exponent β = 1.87 (R2 = 0.996), confirming accelerating deterioration beyond a critical service age. The HPCI inflection coincides with the Grade-2 boundary (3.5–4.0), where surface distress growth—dominated by linear cracking (91.3% of total SD)—also peaks. A LCCA across 44 scenarios demonstrated that PM applied immediately before this acceleration onset minimizes the 40-year net present value (NPV; discount rate 4.5%). The optimal first PM application time was estimated at 10.8 years (≈56% of the 19.3-year average service life), reducing the 40-year NPV by up to 7 million KRW per section relative to the milling and overlay baseline (up to 16 million KRW in absolute NPV terms for concrete overlay sections). These findings provide a quantitative, reproducible basis for PM timing decisions applicable to the approximately 4000 km of expressway pavement managed by Korea Expressway Corporation.

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Publication Details

Journal
Sustainability
Published
2026-04-21
DOI
https://doi.org/10.3390/su18084116
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
Field-Weighted Citation Impact
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article

Optimal Preventive Maintenance Timing for Expressway Asphalt Pavements Based on PMS Deterioration Modeling and Life-Cycle Cost Analysis

Sungho Bae, Kyungnam Kim, Yongdoo Kim, Jinhwan Kim
Sustainability
Infrastructure Maintenance and Monitoring
article

Optimal Preventive Maintenance Timing for Expressway Asphalt Pavements Based on PMS Deterioration Modeling and Life-Cycle Cost Analysis

Sungho Bae, Kyungnam Kim, Yongdoo Kim, Jinhwan Kim
article en

Abstract

The preventive maintenance (PM) of asphalt pavements reduces life-cycle costs and minimizes resource consumption compared with reactive rehabilitation, yet its cost-effectiveness is highly sensitive to application timing. This study develops a data-driven framework for determining optimal PM timing on Korean expressways by integrating network-level pavement management system (PMS) deterioration modeling with life-cycle cost analysis (LCCA). Using 10-year PMS time-series data from approximately 2200 asphalt pavement sections (2012–2021), a nonlinear regression of the Highway Pavement Condition Index (HPCI) yielded an exponential deterioration model with exponent β = 1.87 (R2 = 0.996), confirming accelerating deterioration beyond a critical service age. The HPCI inflection coincides with the Grade-2 boundary (3.5–4.0), where surface distress growth—dominated by linear cracking (91.3% of total SD)—also peaks. A LCCA across 44 scenarios demonstrated that PM applied immediately before this acceleration onset minimizes the 40-year net present value (NPV; discount rate 4.5%). The optimal first PM application time was estimated at 10.8 years (≈56% of the 19.3-year average service life), reducing the 40-year NPV by up to 7 million KRW per section relative to the milling and overlay baseline (up to 16 million KRW in absolute NPV terms for concrete overlay sections). These findings provide a quantitative, reproducible basis for PM timing decisions applicable to the approximately 4000 km of expressway pavement managed by Korea Expressway Corporation.

SustainabilityVol. 18(8)
Seoul National University of Science and Technology (KR), Tech Valley (South Korea) (KR), Korea Telecom (South Korea) (KR)
Decent work and economic growth
Openalex Percentile: Top 9%
Infrastructure Maintenance and Monitoring
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