• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.361-378
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• 2021

While the pavement rating system is being utilized for periodic road condition assessment in the Eastern Region municipality of Saudi Arabia, the condition assessment is costly, time-consuming, and not comprehensive as only few parts of the road are randomly selected for the assessment. Thus, this study is aimed at developing a condition assessment model for a specific sample of a residential road network in Dammam City based on an individual road and a road network. The model was developed using the Analytical Hierarchy Process (AHP) according to the defect types and their levels of severity. The defects were arranged according to four categories: structure, construction, environmental, and miscellaneous, which was adopted from sewer condition coding systems. The developed model was validated by municipality experts and was adjudged to be acceptable and more economical compared to results from the Eastern region municipality (Saudi Arabia) model. The outcome of this paper can assist with the allocation of the government's budget for maintenance and capital programs across all Saudi municipalities through maintaining road infrastructure assets at the required level of services.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.69-76
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• 2018

As for V2I(Vehicle-to-Infrastructure) systems with energy-constrained RSUs(Road Side Units), the previous data delivery strategies have not considered the aspect of energy usage at RSUs. A new data delivery strategy has been proposed to determine the RSU's participation in data delivery based on the probability dependent on the RSU's remaining energy, and it showed the lower data delivery time than the previous approaches. In this paper, we propose methods to analyze the number of RSUs participating in data delivery and the variations of RSUs' energy value for the consecutive data deliveries. As a numerical result, compared with the previous strategy, the probability-based data delivery strategy shows the lower number of participating RSUs and the increased average energy value of all RSUs. In addition, from the analytical results, we propose considerations for the real implementations of the similar systems.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.19-33
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• 2019

There have been enormous efforts to develop an innovative public transport bus service for enhancing its operational efficiency based on Automated Vehicle(AV). However, since the vehicle operating environment in the public transport system varies with the purpose and method of mobility service, it is necessary to preferentially evaluate the current roadworthiness for an effective way to introduce the AV. Therefore, this study classified and redefined AV-based mobility service based on literature reviews. This research conducted the roadworthiness test for checking the feasibilities of the AV-based mobility services. Furthermore, we suggested some deployment strategies of the AV-based mobility service considering the Level-Of-Service (LOS) of road infrastructure based on the results of roadworthiness tests. The proposed direction would have a great potential to introduce the AV-based public transport system in the near future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1723-1728
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• 2021

C-ITS is an intelligent transportation system that can improve transportation convenience and traffic safety by collecting, managing, and providing traffic information between components such as vehicles, road infrastructure, drivers, and pedestrians. In Korea, road infrastructure is being built across the country through the C-ITS project, and various services such as real-time traffic information provision and bus operation management are provided. However, the current state-of-the-art road infrastructure and information linkage system are insufficient to build C-ITS. In this paper, considering the continuity of time in various spatial aspects, we proposed a group-type network-based traffic situation recognition system that can recognize traffic flows and unexpected accidents through information linkage between traffic infrastructures. It is expected that the proposed system can primarily respond to accident detection and warning in the field, and can be utilized as more diverse traffic information services through information linkage with other systems.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.739-744
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• 2005

The construction road work are increasing now. And the domestic slope construction are steadily increased and changed the complicated and large-scale. Therefore ground reinforcement for slope stabilization has been increasingly used during the past few decades with a wide variety of techniques including soil nailing, rock bolt, anchor and different types. But in some cases which applied slope reinforcement construction by badness or mistake. So this paper is the study of construction badness for slope reinforcement.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.825-830
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• 2005

Cut slope and facility of management investigation is the protection of humans and properties. it is very important the prevention of disaster facility and the damage of the slope protection facility. It is very difficult to forecast slope stability, disaster possibility and collapse. It will be able to minimize the damage which it prepare against slope facility and cut slope of deformable investigation and collapse and the disaster. therefore those deformable investigation is important. Investigations execute upheaval, crack, sliding for slope and cut slope reinforcement. Investigation executes forecast in place where the construction problem, the effect which the damage in road traffic or the contiguity facility.

• The Journal of Bigdata
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• v.2 no.2
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• pp.129-140
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• 2017

Weather acts through low visibility, precipitation, high winds, and temperature extremes to affect driver capabilities, vehicle performance (i.e., traction, stability and maneuverability), pavement friction, roadway infrastructure, crash risk, traffic flow, and agency productivity. Recently a variety of road weather big data sources such as CCTV, road sensor/systems, car sensor have been developed to solve the weather-related problems, This study identifies and defines the types and characteristics of these sources to suggest how to utilize them for car safety and efficiency as well as road management through analyzing domestic and oversea cases of road weather big data applications.

• Korean Journal of Construction Engineering and Management
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• v.13 no.4
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• pp.141-151
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• 2012

Infrastructure are the essential element in the country for they are the basic facilities forming the basis of economic activity. In Korea Infrastructure which are subject to the management of government are increasing annually, and subsequently the budget of maintenance costs is expected to rise significantly. For the effective management of the constructed and accumulated infrastructure, the integrated management of the future assets will be needed which includes the determination of the asset status, management subjects, and the location, the maintenance of their performance and state, and the prediction of the cost required to increase their useful lifetime. However, in the domestic cases the road facilities valuation has not been done systematically, and the preparation and research on this is scarce. Thus, the systematic procedure for the road facilities valuation is required. In this paper the following study was conducted to derive the reasonable asset valuation methods. First, the valuation methods was investigated and summarized throughout the domestic and international research literature. Second, to apply the investigated valuation methods to the road facilities the valuation process that reflects domestic conditions and characteristics has been developed. Third, a working Bridge, Highways, and General national ways were applied to the general valuation process, and the results were analyzed. As a final step a schematic diagram of the asset management support by WDRC valuation method was presented.

• 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.

• 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.