• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.89-94
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• 2006

Premature failures in pavements are frequently reported due to rapid increasement in traffic volume, heavy vehicles, and high temperature in the summer. Based on this concept in mind, Korea Highway Corporation established the Test Road Operation Center to estimate the pavement performance. To evaluate the pavement performance effectively using the field data, wandering is an important topic in pavement analysis. In this study, portable wandering system was developed and analyzed to investigate the pavement responses due to the dynamic truck passes, and analyzed the wandering to dynamic load test. The test results revealed that the advantages of laser devices were noticeable compare to the other measuring ones. To understand the behavioral characteristics of pavements using the wandering measurement devices, dynamic truck tests were conducted in the field. Test results showed that the effects of wandering on asphalt pavement were significant. The data analysis using this wandering effect is considered as an important tool in performance analysis of asphalt concrete pavement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2960-2965
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• 2013

Customized services for individuals in analysis of recently collected GPS information have been investigated in various aspects. As the size of collected GPS data gets larger, a variety of services is being released accordingly. Existing studies, however, are limited to presenting service models for users while there is little study on developing intelligent computing technologies in the introduction of GPS information into the system. This study suggests an algorithm to analyze traffic information by introducing GPS information into the system in order to take the lead among intelligent computing technologies. The suggested algorithm analyzes a map by means of the collected vehicle GPS information and sectional traffic information interpretation method; thus, the computer judges the traffic information collected by humans. The experiment result shows that the traffic information was properly analyzed upon the utilization of the given data. Although a small quantity of analyzed data was less reliable, the system maintained high reliability as the data was sufficient.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.649-661
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• 2020

Cut-slope management system (CSMS) has been investigated all slopes on the road of the whole country to evaluate risk rating of each slope. Based on this evaluation, the decision-making for maintenance can be conducted, and this procedure will be helpful to establish a consistent and efficient policy of safe road. CSMS has updated the database of all slopes annually, and this database is constructed based on a basic and detailed investigation. In the database, there are two type of data: first one is an objective data such as slopes' location, height, width, length, and information about underground and bedrock, etc; second one is subjective data, which is decided by experts based on those objective data, e.g., degree of emergency and risk, maintenance solution, etc. The purpose of this study is identifying an data application plan to utilize those CSMS data. For this purpose, logistic regression, which is a basic machine-learning method to construct a prediction model, is performed to predict a judging-type variable (i.e., subjective data) based on objective data. The constructed logistic model shows the accurate prediction, and this model can be used to judge a priority of slopes for detailed investigation. Also, it is anticipated that the prediction model can filter unusual data by comparing with a prediction value.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.3
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• pp.29-37
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• 2008

In this parer, we purpose for applying the RFID(Radio Frequency IDentification) system in National Road Traffic Volume Survey. Because there is limitation for shipping RFID Tag on every car, we firstly defined Expansion (process of making the number of all cars which passed survey point from sampling data) and determined the best methodology among 3 methodologies (Time factor Model, Fuzzy Model, Artificial Neural Network). As a result of analysis, Time Factor Model was chosen as the best methodology for Expansion. Also, we analyzed to find an application of the RFID system in National Road Traffic Volume Survey and obtained a possibility applying it. It is expected that if the RFID system is used in Traffic Volume Survey, the survey cost is saved than before.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.3
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• pp.129-141
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• 2005

It is difficult to edit large-scale digital maps because of problems of cost and process and it is carried out by aerial photogrammetry in renewal periods. Five years of update period cannot provide exact data required in the fast-moving age. This study is to analyze applicability and impact for editing digital map of road system using the GPS-Van. Results are compared with accuracy of the data acquisition with GPS-Van positioning. INS data are affected by the barrier to receive GPS data. But high accuracy were achieved by thorough plans according to work order. By using GPS Van and fieldwork at the same time for editing and renewal of digital map, it is expected that this method can be used to reduce costs in the economic and temporal aspects, and provide rapid and accurate digital map of road system.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.86-99
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• 2021

One of the methods to alleviate traffic congestion is to increase the efficiency of the roads by providing traffic condition information on road user and distributing the traffic. For this, reliability must be guaranteed, and quantitative real-time traffic speed prediction is essential. In this study, and based on analysis of traffic speed related to traffic conditions, historical data correlated with traffic flow were used as input. We developed an LSTM model that predicts speed in response to normal traffic conditions, along with a CNN-LSTM model that predicts speed in response to incidents. Through these models, we try to predict traffic speeds during the hour in five-minute intervals. As a result, predictions had an average error rate of 7.43km/h for normal traffic flows, and an error rate of 7.66km/h for traffic incident flows when there was an incident.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.9-15
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• 2023

In this paper, we propose a method predicting the speed of each lane from the link speed using a neural network. We took three measures for configuring learning data to increase prediction accuracy. The first one is to expand the spatial range of the data source by including 14 links connected to the beginning and end points of the link. We also increased the time interval from 07:00 to 22:00 and included the data generation time in the feature data. Finally, we marked weekdays and holidays. Results of experiments showed that the speed error was reduced by 21.9% from 6.4 km/h to 5.0 km/h for straight lane, by 12.9% from 8.5 km/h to 7.4 km/h for right turns, and by 5.7% from 8.7 km/h to 8.2 km/h for left-turns. As a secondary result, we confirmed that the prediction accuracy of each lane was high for city roads when the traffic flow was congested. The feature of the proposed method is that it predicts traffic conditions for each lane improving the accuracy of prediction.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.21-32
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• 2011

The frost penetration depth of pavement is usually estimated from the freezing index that made temperature data analysis of 30 years and decided the thickness of anti-frost layer. The field monitoring region in study was divided into five regions by freezing index 550~650$^{\circ}C{\cdot}$day, 450~550$^{\circ}C{\cdot}$day and 350~450$^{\circ}C{\cdot}$day. Each region has three-section of road pavement such as cutting area, boundary area of cutting and banking, and lower area of banking. The field monitoring system was established both in the section of anti-frost layer and in the section without anti-frost layer. The data analysis was conducted for determination of frost penetration depth within the paved road by the field monitoring system. The result showed that The temperature of subgrade without anti-frost layer shows below zero in centigrade for the region of freezing index 550~650$^{\circ}C{\cdot}$day, up and down around zero degree in subgrade for the region of freezing index 450~550$^{\circ}C{\cdot}$day, and there is no place existed below zero degree in subgrade for the region of freezing index below 450$^{\circ}C{\cdot}$day. With comparison of field frost penetration depth for the cross-sections of pavement, the cutting area shows the greatest frost penetration depth, and less influence of frost penetration depth for the boundary area of cutting and banking, and the least influenced for the lower area of banking.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.84-93
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• 2004

Recently, domain-specific demands with respect to practical applications and analysis scheme using spatial thematic information are increasing. Accordingly, in this study, GIS-based application program is implemented to perform spatial analysis in transportation geography with base road layer data. Using this program, quantitative estimation of circuity and accessibility, which can be extracted from nodes composed of the graph-typed network structure, in a arbitrary analysis zone or administrative boundary zone is possible. Circuity is a concept to represent the difference extent between actual nodes and fully connected nodes in the analysis zone. While, accessibility can be used to find out extent of accessibility or connectivity between all nodes contained in the analysis zone, judging from inter-connecting status of the whole nodes. In put data of this program, which was implemented in AVX executable extension using AvenueTM of ArcView, is not transportation database information based on transportation data model, but layer data, directly obtaining from digital map sets. It is thought that computation of circuity and accessibility can be used as kinds of spatial analysis functions for GIS applications in the transportation field.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.4
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• pp.461-468
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• 2021

The role of drones is increasing day by day in smart construction that manages construction sites with 3D data in every life cycles. This is because both the digital surface model (DSM) and the orthoimage obtained for the construction site through the drone are made of point cloud data. This study aims to develop standard work types for drone use in order to systematically utilize drones in expressway construction sites. For the study, two expressway construction sites in Korea were set as test beds, and construction types applicable to drones were derived and verified through a pilot project. As a result of the study, three construction work types were developed for road planning, road design and maintenance, respectively, and in road construction, twenty-one detailed construction types were developed for five construction work types. It is expected that drones can be used more systematically not only at expressway construction sites, but also at other road construction sites by utilizing the "standard work type at expressway construction site for drone use" developed in this study.