• Title/Summary/Keyword: Pavement deterioration model

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Internal Property and Stochastic Deterioration Modeling of Total Pavement Condition Index for Transportation Asset Management (도로자산관리를 위한 포장종합평가지수의 속성과 변화과정의 모델링)

  • HAN, Daeseok;DO, Myungsik;KIM, Booil
    • International Journal of Highway Engineering
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    • v.19 no.5
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    • pp.1-11
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    • 2017
  • PURPOSES : This study is aimed at development of a stochastic pavement deterioration forecasting model using National Highway Pavement Condition Index (NHPCI) to support infrastructure asset management. Using this model, the deterioration process regarding life expectancy, deterioration speed change, and reliability were estimated. METHODS : Eight years of Long-Term Pavement Performance (LTPP) data fused with traffic loads (Equivalent Single Axle Loads; ESAL) and structural capacity (Structural Number of Pavement; SNP) were used for the deterioration modeling. As an ideal stochastic model for asset management, Bayesian Markov multi-state exponential hazard model was introduced. RESULTS:The interval of NHPCI was empirically distributed from 8 to 2, and the estimation functions of individual condition indices (crack, rutting, and IRI) in conjunction with the NHPCI index were suggested. The derived deterioration curve shows that life expectancies for the preventive maintenance level was 8.34 years. The general life expectancy was 12.77 years and located in the statistical interval of 11.10-15.58 years at a 95.5% reliability level. CONCLUSIONS : This study originates and contributes to suggesting a simple way to develop a pavement deterioration model using the total condition index that considers road user satisfaction. A definition for level of service system and the corresponding life expectancies are useful for building long-term maintenance plan, especially in Life Cycle Cost Analysis (LCCA) work.

Development of Deterioration Model for Cracks in Asphalt Pavement Using Deep Learning-Based Road Asset Monitoring System (딥러닝 기반의 도로자산 모니터링 시스템을 활용한 아스팔트 도로포장 균열률 파손모델 개발)

  • Park, Jeong-Gwon;Kim, Chang-Hak;Choi, Seung-Hyun;Do, Myung-Sik
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.5
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    • pp.133-148
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    • 2022
  • In this study, a road pavement crack deterioration model was developed for a pavement road sections of the Sejong-city. Data required for model development were acquired using a deep learning-based road asset monitoring system. Road pavement monitoring was conducted on the same sections in 2021 and 2022. The developed model was analyzed by dividing it into a method for estimating the annual average amount of deterioration and a method based on Bayesian Markov Mixture Hazard model. As a result of the analysis, it was found that an analysis results similar to the crack deterioration model developed based on the data acquired from the Automatic pavement investigation equipmen was derived. The results of this study are expected to be used as basic data by local governments to establish road management plans.

Methodology for Benefit Evaluation according to Maintenance Method and Timing of National Highway Pavement Section (국도포장 유지보수 공법 및 시기에 따른 편익산정 방안)

  • Do, Myungsik;Kwon, Soo Ahn;Choi, Seunghyun
    • International Journal of Highway Engineering
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    • v.15 no.5
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    • pp.91-99
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    • 2013
  • PURPOSES : This study aims at proposing the methodology for benefit evaluations in pavement maintenance methods and timings using KoPMS(Korean Pavement Management System) software which was developed for efficient pavement management. METHODS : This study classified pavement sections into 4 clusters considering AADT(Annual Average Daily Traffic) and ESAL(Equivalent Single-Axle Load) using cluster analysis and used the deterioration models in each cluster. Increased user costs due to pavement deterioration as time goes by and agent costs for maintenance were estimated. Based on deterioration model and KoPMS software, Methodology for benefit evaluation was proposed in pavement maintenance methods and with/without implementation using real pavement section data. RESULTS : This study verified that considering agent costs only would be constrained to decide pavement maintenance methods and timings, and ascertained that decision making with agent and user costs would be effective. In addition, this study revealed that pavement maintenance methods and timings can be affected by AADT and ESAL and frequent pavement maintenances can be more efficient for benefits in pavement sections with more AADT and ESAL. Also this study found that user costs would be more affected to decision making than agent costs. Moreover, Delay of conducting pavement maintenance caused increased vehicle operating costs and environmental costs because of poor conditions of pavements. CONCLUSIONS : This study proposed LCCA and benefit estimation methodology of pavement with considering agent and user costs. The results of this study can be used for baseline data of efficient pavement asset management.

Application of Markov Chains and Monte Carlo Simulations for Pavement Construction Engineering

  • Nega, Ainalem;Gedafa, Daba
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1043-1050
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    • 2022
  • Markov chains and Monte Carlo Simulation were applied to account for the probabilistic nature of pavement deterioration over time using data collected in the field. The primary purpose of this study was to evaluate pavement network performance of Western Australia (WA) by applying the existing pavement management tools relevant to WA road construction networks. Two approaches were used to analyze the pavement networks: evaluating current pavement performance data to assess WA State Road networks and predicting the future states using past and current pavement data. The Markov chains process and Monte Carlo Simulation methods were used to predicting future conditions. The results indicated that Markov chains and Monte Carlo Simulation prediction models perform well compared to pavement performance data from the last four decades. The results also revealed the impact of design, traffic demand, and climate and construction standards on urban pavement performance. This study recommends an appropriate and effective pavement engineering management system for proper pavement design and analysis, preliminary planning, future pavement maintenance and rehabilitation, service life, and sustainable pavement construction functionality.

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Development of Prediction Method for Highway Pavement Condition (포장상태 예측방법 개선에 관한 연구)

  • Park, Sang-Wook;Suh, Young-Chan;Chung, Chul-Gi
    • International Journal of Highway Engineering
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    • v.10 no.3
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    • pp.199-208
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    • 2008
  • Prediction the performance of pavement provides proper information to an agency on decision-making process; especially evaluating the pavement performance and prioritizing the work plan. To date, there are a number of approaches to predict the future deterioration of pavements. However, there are some limitation to proper prediction of the pavement service life. In this paper, pavement performance model and pavement condition prediction model are developed in order to improve pavement condition prediction method. The prediction model of pavement condition through the regression analysis of real pavement condition is based on the probability distribution of pavement condition, which set to 5%, 15%, 25% and 50%, by condition of the pavement and traffic volume. The pavement prediction model presented from the behavior of individual pavement condition which are set to 5%, 15%, 25% and 50% of probability distribution. The performance of the prediction model is evaluated from analyzing the average, standard deviation of HPCI, and the percentage of HPCI which is lower than 3.0 of comparable section. In this paper, we will suggest the more rational method to determine the future pavement conditions, including the probabilistic duration and deterministic modeling methods regarding the impact of traffic volume, age, and the type of the pavement.

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Development of the Decision-Making System for National Highway Pavement Management (국도 포장관리를 위한 의사결정시스템 개발)

  • Do, Myungsik;Kwon, Sooahn;Lee, Sang Hyuk;Kim, Yongjoo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.34 no.2
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    • pp.645-654
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    • 2014
  • PMS (Pavement Management System) of National highways in Korea has used HDM (Highway Development and Management)-4 developed by World Bank for decision-making for maintenance and rehabilitation of pavements. However using HDM-4 is not appropriate in Korea because HDM-4 requires excessive input factors for analysis and economic analysis models loaded in HDM-4 are not suitable for Korean circumstances. Thus this study aims development of decision-making system for effective pavement management with reflecting Korean circumstances. Moreover this study proposed to define component of system, deterioration models, and basic units for component, and to analyze characteristics of component of system, and also to develop optimal decision-making system. The decision-making system for PMS mainly consists of 1) DB of highways, traffics, and socio-economic index, 2) pavement deterioration model, 3) speed prediction models by pavement conditions, 4) economic evaluation models, and 5) decision-making supporting system. Also this study provided analysis results in case studies for system verifications. However pavement deterioration models considering future probabilistic characteristic and index of decision-making are needed to develop for a further study.

Development of Deep Learning Based Deterioration Prediction Model for the Maintenance Planning of Highway Pavement (도로포장의 유지관리 계획 수립을 위한 딥러닝 기반 열화 예측 모델 개발)

  • Lee, Yongjun;Sun, Jongwan;Lee, Minjae
    • Korean Journal of Construction Engineering and Management
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    • v.20 no.6
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    • pp.34-43
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    • 2019
  • The maintenance cost for road pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance preventive maintenance requires the establishment of a strategic plan through accurate prediction of road pavement. Hence, In this study, the deep neural network(DNN) and the recurrent neural network(RNN) were used in order to develop the expressway pavement damage prediction model. A superior model among these two network models was then suggested by comparing and analyzing their performance. In order to solve the RNN's vanishing gradient problem, the LSTM (Long short-term memory) circuits which are a more complicated form of the RNN structure were used. The learning result showed that the RMSE value of the RNN-LSTM model was 0.102 which was lower than the RMSE value of the DNN model, indicating that the performance of the RNN-LSTM model was superior. In addition, high accuracy of the RNN-LSTM model was verified through the comparison between the estimated average road pavement condition and the actually measured road pavement condition of the target section over time.

Infrastructure Health Monitoring and Economic Analysis for Road Asset Management : Focused on Sejong City (도로 자산관리를 위한 상태 모니터링 및 경제성 분석 : 세종시를 중심으로)

  • Choi, Seung-Hyun;Park, Jeong-Gwon;Do, Myung-Sik
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.4
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    • pp.71-82
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    • 2021
  • In this study, a novel method for monitoring road pavements using the Mobile Mapping System (MMS) and a deep learning crack detection system was presented. Furthermore, an optimal maintenance method through economic analysis was presented targeting the pavement section of Sejong City. As a result of monitoring the pavement conditions, it was confirmed that the pavement ratings were good in the order of national highways, municipal roads, and roads of provinces. In addition, economic analysis using the pavement deterioration model showed that micro-surfacing, one of the preventive maintenance methods, is the most economical in terms of maintenance costs and user benefits. The results of this study are expected to be used as fundamental reference for local governments' infrastructure management plans.

Case Study on Deciding a Time for Repairing Asphalt Pavement of Incheon International Airport (인천국제공항 아스팔트 포장 보수시기 결정 사례 연구)

  • Lee, Jae-Ho;Kim, Jang-Rack;Mun, Hyung-Chul;Cho, Nam-Hyun
    • International Journal of Highway Engineering
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    • v.15 no.6
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    • pp.49-60
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    • 2013
  • PURPOSES : The evaluation of the pavement condition of the asphalt concrete pavement of No. 2 runway of Inchon International Airport through PMS, a supporting system for making a decision of pavement, maintenance and repair, was made, and the proper time for repair according to the PCI reduction rate was suggested. METHODS : By comparing and analyzing the evaluation results of pavements built in 2009, 2010, 2011, PCI change in each facility (No. 2 runway, C parallel taxiway, connection taxiway) was calculated. By applying the calculated change to PCI deduction rate model, the pavement condition of the target sections was estimated, and then the necessary section and time for repair were chosen. RESULTS : After careful consideration of the time for pavement and maintenance, based on the result of PCI prediction, it was estimated that the southern takeoff and landing section of No. 2 runway was required to be repaired in 2012; connection taxiway in 2013; and C parallel taxiway in 2014; however, the section which is the main moving route of connection taxiway and C parallel taxiway was needed to be repaired in 2012. CONCLUSIONS : For maintenance and repair of airport pavements, the optimal alternative should be chosen by considering economics and operability, via examining the time for repair and the aspect of management all together on the basis of this study.

Development of Seocho Borough Pavement Condition Evaluation Model based on Seoul Metropolitan SPI (서울시도 SPI를 활용한 서초구 도로포장상태 평가모형 개발)

  • Lee, Sang-Yum;Park, Mi-Youn;Kim, Kyoon-Tai
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.11
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    • pp.314-321
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    • 2016
  • Adapting the maintenance criteria of Seoul City pavement is not applicable for borough pavement due to differences between the pavement of Seoul city and the borough, such as priority of maintenance, traffic volume, thickness of pavement, and pavement deterioration rate by distresses. To develop an efficient and reasonable evaluation method of the Seocho borough pavement condition within a limited budget, this study suggested the borough pavement condition evaluation model based on the PMS (Pavement Management System) of Seoul Metropolitan SPI (Seoul Pavement Index). The SPI was modified to predict the remaining life and determine the proper maintenance method for the pavement in Seocho borough. This was suggested to reflect the rate of the designed performance life and field performance life of pavement as well as the pavement condition at the stage of the completion of construction. Primary variables, such as crack, rutting and IRI in the final model affect the overall performance life due to their even composition. Therefore, the suggested model considering the lowered criteria, design performance factor, and construction factor can be used for the more efficient maintenance of Seocho borough pavement.