• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1639-1650
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• 2013

Road pavement management is an important activity that affects to national economy, movement and safety of people, and also demands huge amount of budget. Therefore, its management strategy must be established under objective information. In addition, decision support system that produces the management strategy needs to consider practical benefits from various aspects. Considering these aspects, this paper aimed to develop a customized Korean life cycle cost analysis model estimating various effects on road users and socio-environmental costs based on pavement condition. The suggested LCCA model focused on Korean national highway, and tried to adopt a national guideline recommended by Korean government for securing credibility of estimation results. In the development processes, some of the suggestions that do not fit well in the situations of pavement management field were added, altered, or partially modified. These attempts to develop customized asset management system would be an important step to break away from passive attitudes relying on ready-made software, but also to improve awareness about the social benefits from the better maintenance strategy.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.469-470
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• 2011

국도는 사회간접자본 중 하나로서 지속적으로 관리되어야 그 기능을 발휘할 수 있는 국가의 중요한 자산이다. 지금까지는 국도를 포장관리시스템이라는 체계로 관리하여왔다. 이 포장관리시스템은 시설물유지관리차원에서 사회기반시설을 관리하는 것으로서 주로 관리자 관점에서 공학적 판단을 기준으로 최소의 비용으로 공용수명을 최대화하는 모델이다. 그러나 경제발전으로 국민의 소득수준이 올라감에 따라 기본적인 욕구가 해결되어 이제는 납세자로서 국민의 동의는 국가의 정책을 결정하는데 중요한 변수로 작용하기 시작했다. 따라서 사용자 관점의 평가는 이러한 요구의 수준을 측정할 수 있는 중요한 척도가 되었으며 이에 기반한 LoS(Level of Service, 서비스 수준)라는 지수를 시설물 자산관리에 활용하려는 여러 가지 시도가 있다. 이 논문에서는 기존 국도포장관리시스템의 정보모델과 KTAM-40(Korea Total Asset Management-40)이라는 자산관리 정보모델을 비교하여 LoS의 필요성과 도로포장자산관리에서 LoS가 사용자 관점을 반영하는 방식을 조명해 이의 장점을 밝히고자 한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.663-673
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• 2010

We are developing asset management information systems to introduce the preventive/proactive approach at operation and management (O&M) of infrastructures. The objective of this study is to explore the future direction for development and operation of asset management information systems. So, we developed the success model and selected the evaluation criteria for analyzing user satisfaction to assess the expected performance of asset management information systems and the degree of impact on asset management functions to operation and management of highway transportation facilities. We estimated the relative importance weight according to the selected evaluation criteria through AHP analysis. We verified the logical consistency of the importance weight and exclude biased outlier from importance weight group using the concept of the Compatibility.

• Transportation Technology and Policy
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• v.4 no.2
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• pp.140-147
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• 2007

• 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.

• International Journal of Highway Engineering
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• v.10 no.3
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• pp.231-237
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• 2008

One of the basic requirements for the most advanced countries would be the well-planned traffic infrastructures. For such traffic safety systems, foreign countries follow the current tendency to which they manage the traffic facilities and equipments based on the objective assessment for the state of every traffic safety facility in terms of Asset Management(AM). As the road safety facilities related among them are very diverse, and their functions are very important as well, the regulations and directions for installing them are enacted. However, despite the standards and directions for the installations, sometimes, the facilities are not installed in accordance with the standards, not only causing inconvenience to the users but also negatively affecting the safety for them. In the study, for the facilities in which the installation interval and height are standardized according to the designed speed and geometrical structure of the road among the various road safety facilities, the image analysis model capable of measuring them with a line scanning camera was developed. In addition, the program systematically analyzing this was also developed and applied to the field and, as the result of that, the size and installation interval of the facilities could be measured fast and accurately.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.423-424
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• 2012

기존에 운영되고 있는 공공시설관리 시스템들을 효율적으로 관리하기 위해서는 유지관리 모형이 표준화되어 범정부EA 지원시스템에 목표아키텍처로 등록되고 더 나아가서는 범정부 표준시스템으로 만들어 필요한 기관에 보급할 필요가 있다. 이 연구에서는 도로, 터널, 철도 등 인프라 시설관리 정보시스템을 구축하는데 필수적인 성과참조모델을 범정부EA 관점에서 제시하였다. 제시한 참조모델을 기준으로한 자산관리모형 아키텍처 모습이 GEAP에 등록 관리 된다면 이것을 바탕으로 타 기관에서 향후 정보시스템을 구축할 때 사전에 파악하고 활용하도록 제안 할 수 있을 것이다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.587-598
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• 2012

Successful implementation of infrastructure asset management system can be started with rich and reliable data. However, measurement errors in the data have always existed in the real world caused for many unknown reasons. It disturbs maintenance activities of agencies, and makes negative effects to reliability of research results on forecasting deterioration process and life cycle cost. Above all, it makes a contradiction that road agencies cannot believe their inspection data surveyed by their hands. It is particularly serious in the road pavement management field. Although road agencies are well recognized the fact, inspecting without measurement error would be a great challenge. Considering the facts, this paper aimed to suggest statistical error processing methods to correct latent error included in pavement surface inspection data. As alternatives, this paper suggested two methods based on probability distribution to consider structure of error and reliability of the data. The suggested methods were empirically tested by using pavement inspection data from Korean National Highway. As the result, this paper confirmed that conventional error processing that just removes only visible errors is not enough to cover uncertainty in pavement deterioration process. The suggested methods would be useful for improving reliability of analysis results required for road infrastructure asset management.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.155-163
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• 2019

This paper proposes a new methodology to recognize cracks on asphalt road surfaces using the image data obtained with drones. The target section was Yuseong-daero, the main highway of Daejeon. Furthermore, two object detection algorithms, such as Tiny-YOLO-V2 and Faster-RCNN, were used to recognize cracks on road surfaces, classify the crack types, and compare the experimental results. As a result, mean average precision of Faster-RCNN and Tiny-YOLO-V2 was 71% and 33%, respectively. The Faster-RCNN algorithm, 2Stage Detection, showed better performance in identifying and separating road surface cracks than the Yolo algorithm, 1Stage Detection. In the future, it will be possible to prepare a plan for building an infrastructure asset-management system using drones and AI crack detection systems. An efficient and economical road-maintenance decision-support system will be established and an operating environment will be produced.

• 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.