• International Journal of Highway Engineering
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• v.14 no.6
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• pp.57-65
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• 2012

PURPOSES : Efficiency Improvement of a public road construction project management work using the development of a real-time remote site monitoring system METHODS : In this study, we developed the remote site monitoring system using a web camera for road construction projects in the RCMA(Regional Construction Management Administration). We can be monitored a construction progress and a weak point of the situation in real time using this. To achieve this, we tested about 10 road construction projects ordered by RCMA. Then, we verified a applicability for the site monitoring system in future. RESULTS : Take advantage of the remote site monitoring system consists of the Construction CALS System, one of the business systems used in the part of the MLTM(Ministry of Land, Transport and Maritime Affairs) institution-agencies. Was configured to be served through the "Construction CALS System" of "Construction Management System(Contractors)" and the "Construction CALS Portal System". Through this, Benefit analysis through a pilot application of the 10 road construction sites and developing considerations and "Guide for visual information processing equipment installation-operating in construction sites"are presented. CONCLUSIONS : Through the establishment of remote site monitoring system can improve the efficiency of construction management services. In addition, Various disasters and calamities, accidents and illegal construction will be prevented in advance is expected. This is expected to further improve the quality of the facilities.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.27-33
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• 2014

This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately 160,000 road signs installed along the highways, national roadways, and local roads in the cities, districts (gun), and provinces (do) of Korea. RReP is based on GPS(Global Positioning System), IMU(Inertial Measurement Unit), INS(Inertial Navigation System), DMI(Distance Measurement Instrument), and lasers, and uses an imagery information collection/classification module to allow the automatic recognition of signs, the collection of shapes, pole locations, and sign-type data, and the creation of road sign registers, by extracting basic data related to the shape and sign content, and automated database design. Image division and merging, which were applied in this study, produce superior results compared with local binarization method in terms of speed. At the results, larger texts area were found in images, the accuracy of text recognition was improved when images had been gradated. Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.222-232
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• 2019

Mongolia is a developing country with a smaller population living across a large territory where infrastructure is underdeveloped. The country has been actively implementing road construction in recent years. The Mongolian government has increased investments in new road construction, but funding for major maintenance or reconstruction projects declined between 2012 and 2016. On the other hand, road network management has not been implemented owing to insufficient road maintenance and If the road network expands, there is a risk that the cost of overall maintenance will increase significantly in the future. Therefore, in order to cope with these problems, this study reviewed applying Korean road model to Mongolia for systematic management of road infrastructure.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.95-105
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• 2021

Road surface damage detection is essential for a comfortable driving environment and the prevention of safety accidents. Road management institutes are using automated technology-based inspection equipment and systems. As one of these automation technologies, a sensor to detect road surface damage plays an important role. For this purpose, several studies on sensors using deep learning have been conducted in recent years. Road images and label images are needed to develop such deep learning algorithms. On the other hand, considerable time and labor will be needed to secure label images. In this paper, the adversarial learning method, one of the semi-supervised learning techniques, was proposed to solve this problem. For its implementation, a lightweight deep neural network model was trained using 5,327 road images and 1,327 label images. After experimenting with 400 road images, a model with a mean intersection over a union of 80.54% and an F1 score of 77.85% was developed. Through this, a technology that can improve recognition performance by adding only road images was developed to learning without label images and is expected to be used as a technology for road surface management in the future.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.46-53
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• 2008

• Journal of the Korean Society of Safety
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• v.24 no.5
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• pp.113-121
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• 2009

The objective of this study is to develop highway advisory radio service for road safety oriented system design of the point by regional groups or geographical distributions. To develop these highway advisory radio service, traffic information provided service areas, responds for incident and accident, and road condition in service sections based on traffic information of highway advisory radio service. This study contributes to service of traffic information for safety driving, which is transport congestion areas and recognition of traffic congestion status in advanced traffic information service. As result of this study, systematic design of the advanced highway and traffic safety guides to management systems by highway advisory radio service.

• Journal of the Korean Professional Engineers Association
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• v.33 no.4
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• pp.38-43
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• 2000

ITS(Intelligent Transport System), a technology based on the recent and remarkable development in control, communications, computer and general information technologies is generally expected to be the most promising solution to the traffic congestion on urban road networks. The objective of this paper is to suggest the plan of ITS information service, current trends of ITS strategy, and technology standards.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.6
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• pp.91-99
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• 2015

This study intends to build a traffic accident predictive model considering road geometrics, traffic and enviromental characteristics and identify the relationship of 4-legs intersection accidents in Seoul and Busan metropolitan area. The RPNB(Random Parameter Negative Binomial) model shows improvement over the fixed NB(Negative Binomial) and out of 53 variables, 10 variables (main road number of lane, main road vehicle traffic volume(left), minor road vehicle traffic volume(right), main road drive restriction, minor road sight distance, minor road median strip, minor road speed limit, minor road speed restriction) showed to have significant variables affecting traffic accident occurrences in 4-legs signilized intersections. Also, among 10 significant variables, 2 variables(minor road sight distance, minor road speed restriction) found to be random parameters.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.114-128
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• 2013

Greenhouse gas emissions have been an important issue in different countries because of their effects on global warming. The government has to organize greenhouse gas reduction measures suitable to regional characteristics by establishing annual implementation plans and comprehensive policies based on the UNFCCC. The transportation sector is one of the major contributors of air pollution; hence increasing need to estimate current and future traffic emissions precisely. Under these circumstances, a number of emission models have been developed recently. However, current methods of estimation cannot carry out effective analyses because it does not reflect vehicle movement characteristics. This study aims to present a new method for calculating road traffic emissions in Goyang city. A travel demand model is utilized to carry out GHG emission estimates according the traffic data (fleet composition, vehicle kilometers travelled, traffic intensity, road type, emission factors and speed). This study evaluates two approaches to estimate the road traffic emissions in Goyang City: Pollution-Emis and the Handbook of Emission Factors for Road Transport (HBEFA v.3.1) which is representative of the "average speed" and the "traffic situation" model types. The evaluation of results shows that the proposed emission estimation method may be a good practice if vigilant implementation of model inputs is observed.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.2_spc
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• pp.275-289
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• 2020

In 2017, multimodal transportation tests for evaluating road, sea, and rail transport were performed by research institutes in the US, Spain, and the Republic of Korea. In this study, acceleration and strain data determined through road and sea tests were analyzed. It was investigated whether the load generated for each transport mode was amplified or attenuated according to the load transfer path. From the results, it was confirmed that the load transfer characteristics differed according to the transportation mode and loading path. The effects of strain determined through each test on the structural integrity of the spent nuclear fuel were also investigated. It was found that the magnitude of the measured strain had a negligible effect on the structural integrity of the spent nuclear fuel, considering its fatigue strength. The results for the acceleration and strain data analyses obtained in this study will be useful for scheduled domestic transportation tests under normal transport conditions.