• Journal of Korean Society for Geospatial Information Science
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• v.10 no.4 s.22
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• pp.77-84
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• 2002

Recently, damage of pavement represented by crack is depened by the increase of traffic demand up to ten million and wight, and interest about the efficient management of pavement is being increased gradually according to the growth of maintenance expense of road surface. In this study, the possibility of application for acquisition of crack information was tested by appling DCRP and digital image processing technique and measuring crack on road surface precisely. Based on this, objective and efficient road surface measurement was planned and done. Measuring crack width, acquire result of comparative high accuracy. So, it is considered that it can be utilized as plan draft data for deterioration estimation and repair reinforcement work of pavement.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.8
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• pp.233-247
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• 1999

Traffic accidents are normally caused by late or faulty judgements due to the driver's inaccurate estimation of the distance, velocity, and acceleration from the surrounding vehicles as well as his carelessness or inattention. Thus, the development of collision avoidance systems is motivated by their great potential for increased vehicle safety. A typical collision avoidance system consists of the forward-looking sensor, the criteria for activation of collision warming and avoidance, the collision avoidance maneuvers, and the user interface. This thesis is concerned with the development of a collision warning algorithm in which the driver is warned of approaching collision with the visual and/or the audible signals . The warning algorithm based on fuzzy logic is presented here based on new warning criteria. It has been newly derived from the conventional warning equation by adding a new input variable of the required deceleration to avoid collision. The algorithm is also able to adapt to the individual driver's taste along with the different road conditions by externally controlling the warning intensity. Finally , the proposed algorithm has been validated using computer simulation.

• Smart Structures and Systems
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• v.32 no.1
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• pp.49-59
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• 2023

A bridge transportation network supplies products from various source nodes to destination nodes through bridge structures in a target region. However, recent frequent earthquakes have caused damage to bridge structures, resulting in extreme direct damage to the target area as well as indirect damage to other lifeline structures. Therefore, in this study, a surrogate model-based comprehensive framework to estimate the seismic resilience of bridge transportation networks is proposed. For this purpose, total system travel time (TSTT) is introduced for accurate performance indicator of the bridge transportation network, and an artificial neural network (ANN)-based surrogate model is constructed to reduce traffic analysis time for high-dimensional TSTT computation. The proposed framework includes procedures for constructing an ANN-based surrogate model to accelerate network performance computation, as well as conventional procedures such as direct Monte Carlo simulation (MCS) calculation and bridge restoration calculation. To demonstrate the proposed framework, Pohang bridge transportation network is reconstructed based on geographic information system (GIS) data, and an ANN model is constructed with the damage states of the transportation network and TSTT using the representative earthquake epicenter in the target area. For obtaining the seismic resilience curve of the Pohang region, five epicenters are considered, with earthquake magnitudes 6.0 to 8.0, and the direct and indirect damages of the bridge transportation network are evaluated. Thus, it is concluded that the proposed surrogate model-based framework can efficiently evaluate the seismic resilience of a high-dimensional bridge transportation network, and also it can be used for decision-making to minimize damage.

• Journal of Korean Society of Transportation
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• v.20 no.2
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• pp.27-38
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• 2002

This study estimates the social cost of the traffic congestion of the Express highway from Seoul to Pusan during the New Year holiday in 1999. Considering inelastic demand and the hyper congestion, we show the congestion cost can be estimated as externalities caused by traffics which exceed the road capacity. Due to the congestion, it is estimated that it took about 12.40 hours more from Seoul to Pusan. The congestion is also estimated to have caused fuel cost of 0.6 billion won. time cost of 43.6 billion won and environmental cost of 0.5 billion won. The total cost reached up to 44.8 billion won.

• Journal of Digital Contents Society
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• v.8 no.1
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• pp.77-83
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• 2007

The handoff area is the region where a call can be handled by the base station in any of the adjacent cells, and duration time is viewed as the time a mobile station resides in the handoff area. In this paper, probability distribution about hand off time one of important parameter at traffic modelling in mobile communication system was estimated. First, point statistic is applied using sample data obtained from simulation result to choose the group of distribution of handoff duration time. Second, parameters are estimated to decide specific distribution function. For this, the value of parameters is calculated using MLE(Maximum Likelihood Estimate.) and goodness of fit test is performed. finally these results show that handoff duration time follows gamma distribution.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.37-43
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• 2003

The purpose of this thesis is to detect multiple vehicles using sequence image analysis at process that detect forward vehicles and lane from sequential color images. Detection of vehicles candidate area uses shadow characteristic and edge information in one frame. And, method to detect multiple vehicles area analyzes Estimation of Vehicle(EOV) and Accumulated Similarity Function(ASF) of vehicles candidate areas that exist in sequential images and examine possibility to be vehicles. Most researches detected a forward vehicles in road images but this research presented method to detect several vehicles and apply enough in havy traffic. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and present the results such as processing time, accuracy and vehicles detection in the images.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.

• Proceedings of KOSOMES biannual meeting
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• 2008.05a
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• pp.69-74
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• 2008

The aim of this paper is to calculation benefit cost for development of Hwawon leisure & tourism complex. To calculation benefit cost, this paper propose a advanced travel cost method(ATCM) which is to consider Improved travel cost method(ITCM) and variable traffic units with confidence degree cf decision-maker. At the result of calculation, total benefit costs are 292805 million won at 52% of confidence degrees and 10% discount rates.. Also total benefit cost is 304517 million won at 4% of GDP growth rate is 4%.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1736-1746
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• 2008

Because present road traffic reaches to the limitation of its faculty, Korean tilting train was developed to find the solution by increasing the speed of rail road. A tilting train can run on a curved rail at high speed so it improves a speed of a rail transit without constructing a new line. Only minimum modification is necessary for a existing line. According to above requirement, Korean tilting train was developed in 2007 and the try run has been executing since April, 2007 in order to validate its safety and reliability in a service lines. And this test and estimation will be completed in 2009. After completing a try run, main parts of tilting train will be studied again to commercialize and localize including a bogie and its commercial model design will be finalized by 2012. In order to achieve the development target as mentioned above, the study have been done to improve the bogie system. As the first step to design commercialized bogie system, measurements from the try run and a dynamic analysis were used to find problems of present bogie system well. So this project is performed to decide what parts of the bogie should be modified in basis of this result.

• Nuclear Engineering and Technology
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• v.53 no.6
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• pp.1979-1990
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• 2021

Evacuation Time Estimate (ETE) can provide decision-makers with a likelihood to implement evacuation of a population with radiation exposure risk by a nuclear power plant. Thus, the ETE is essential for developing an emergency response preparedness. However, studies on ETE have not been conducted adequately in Korea to date. In this study, different cohorts were selected based on assumptions. Existing local data were collected to construct a multi-model network by TSIS-CORSIM code. Furthermore, several links were aggregated to make simple calculations, and post-processing was conducted for dealing with the stochastic property of TSIS-CORSIM. The average speed of each cohort was calculated by the link aggregation and post-processing, and the evacuation time was estimated. As a result, the average cohort-based evacuation time was estimated as 2.4-6.8 h, and the average clearance time from ten simulations in 26 km was calculated as 27.3 h. Through this study, uncertainty factors to ETE results, such as classifying cohorts, degree of model complexity, traffic volume outside of the network, were identified. Various studies related to these factors will be needed to improve ETE's methodology and obtain the reliability of ETE results.