• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.251-253
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• 2022

관제구역내 충돌사고 예방을 위해 어선에 대한 안전관리가 중요시 되고 있으며 이들 어선들의 조업 패턴 분석 및 충돌 위험평가를 통해 위험 구역을 설정, 설정된 구역 내에서의 사고 예방을 위한 효율적 관제 방안 마련하였다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.06a
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• pp.147-148
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• 2010

최근 타 교통수단으로 인해 발생하는 교통사고나 환경오염 등의 문제들을 보완하는 녹색 교통수단의 하나로써 보행교통에 대한 관심과 연구가 활발하게 증가되고 있다. 하지만 차량교통에 관한 연구에 비해 보행 교통에 관한 연구는 미미하며, 특히 우리나라 여건에 맞는 보행 환경의 서비스 수준과 보행 안전도 등에 대한 객관적 평가 모형의 개발이 필요한 실정이다. 이에 본 연구에서는 도시 내 보행 환경 요소를 정량적으로 계산하고 측정할 수 있는 평가 지표인 그린 스코어(Green Score)를 개발하고자 하였다. 본 논문에서 제시한 그린 스코어 측정 모형은 실제 물리적인 보행공간을 기반으로 가상의 시스템에 적용되어 보행 이동 패턴의 가시화, 보행 환경의 쾌적성과 편의성 평가 예측에 활용될 수 있을 것이다.

• Journal of Korean Society of Transportation
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• v.13 no.2
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• pp.19-42
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• 1995

1980년대 후기부터 교통정책의 우선 목표는 지역경제성장 자체가 교통문제를 스스로 해결할 수 있도록 하기 위하여 종래의 관리 중시의 정책은 다시 토지이용 정책으로 변화를 초래하엿다. 오늘날 대도시는 개개 졍제활동 주체들의 동적인 경제 행태에근거하여 분산구조를 띠고 있다. 이러한 동적인 경제행태에 미치는 요소들은 교통체계와 토지이용과 상호연관성의 연구에 필수적인 지가, 인구분포, 통행행태등이다. 그러나 전통적인 단핵도시 모형은 대도시의 분산구조형태의 동적인 과정을 설명하는데는 한계가 있다. 본 연구는 대도시의 변천과정을-도심 및 부심의 출현·소멸현상-설명함으로써 도시교통정책 필수적인 입지와 통행패턴에 대한 새로운 동태적 이론의 기초를 제공하는데 그 목적이 있다. 이를 위하여 지역경제 성장과 도시공간구조와의 동태적관계를 통합하는 토지이용과 교통의 연속 모형을 개발·응용하였다. 개발된 모형에서는 교통량에 따른 교통비용, 도시공간구조로 인한 외부효과들, 경제활동주체들의 비동질성, 이주비용, 그리고 집적 이익등이 매기마다 내생적으로 결정되어 대도시의 공간구조 변화를 설명한다. 경제 호라동주체들간의 ? 호물리적 교류는 소득 증대에 의하여 경제구조가 변함에 따라 새로이 결정된다. 가상적 도시와 자료를 가지고 실험한 결과 비동질적인 경제주체들의 불균형적 성장이 장기적으로 도시구조에 영향을 미치며, 기본적인 경제행위에 따라 장기동태적인 과정을 통하여나타나는 도시의 분산구조형태의 중요성을 보여주고 있다. 또한 교통비용의 변화에 따른 민감도분석을 통하여 모형의 실용성을 검정하였다.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.44-63
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• 2007

The purpose of this study is to propose mining processes in the large trip-transaction database of the Metropolitan Seoul area and to analyze the spatial characteristics of travel behavior. For the purpose. this study introduces a mining algorithm developed for exploring trip patterns from the large trip-transaction database produced every day by transit users in the Metropolitan Seoul area. The algorithm computes trip chains of transit users by using the bus routes and a graph of the subway stops in the Seoul subway network. We explore the transfer frequency of the transit users in their trip chains in a day transaction database of three different years. We find the number of transit users who transfer to other bus or subway is increasing yearly. From the trip chains of the large trip-transaction database, trip patterns are mined to analyze how transit users travel in the public transportation system. The mining algorithm is a kind of level-wise approaches to find frequent trip patterns. The resulting frequent patterns are illustrated to show top-ranked subway stations and bus stops in their supports. From the outputs, we explore the travel patterns of three different time zones in a day. We obtain sufficient differences in the spatial structures in the travel patterns of origin and destination depending on time zones. In order to examine the changes in the travel patterns along time, we apply the algorithm to one day data per year since 2004. The results are visualized by utilizing GIS, and then the spatial characteristics of travel patterns are analyzed. The spatial distribution of trip origins and destinations shows the sharp distinction among time zones.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.105-115
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• 2011

In Vision-based Intelligent Transportation System(ITS) the segmentation of road region is a very basic functionality. Accordingly, in this paper, we propose a region segmentation method using adaptive pattern extraction technique to segment road regions and sky regions from original images. The proposed method consists of three steps; firstly we perform the initial segmentation using Mean Shift algorithm, the second step is the candidate region selection based on a static-pattern matching technique and the third is the region growing step based on a dynamic-pattern matching technique. The proposed method is able to get more reliable results than the classic region segmentation methods which are based on existing split and merge strategy. The reason for the better results is because we use adaptive patterns extracted from neighboring regions of the current segmented regions to measure the region homogeneity. To evaluate advantages of the proposed method, we compared our method with the classical pattern matching method using static-patterns. In the experiments, the proposed method was proved that the better performance of 8.12% was achieved when we used adaptive patterns instead of static-patterns. We expect that the proposed method can segment road and sky areas in the various road condition in stable, and take an important role in the vision-based ITS applications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3508-3517
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• 2013

District is not only a place that every urban activities are executing but also basic unit that are forming urban structure. Therefore this study tried to make land use-transportation model through analyzing $CO_2$ exhausting volumes by assuming 270 scenarios those are postulated various land use patterns and transport policies in District. As results, this study shows best District Unit Design technique is the policy that develop equally all blocks or only outer blocks and introduction of car free zone to inner 2 way streets. Most important policy in order to reduce $CO_2$ gas is to introduce Transportation Demand Management especially in case of hyper high density development. In case of low density development, policy of car free streets in 2 ways roads is efficiency for reducing $CO_2$ gas. And suggested land use-transportation model will be good for choosing alternatives those are able to reduce $CO_2$ in District Unit.

• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.121-132
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• 2007

Up to now Permanent traffic volumes have been counted by Automatic Vehicle Classification (AVC) on National Highways. When counted data have missing items or errors, the data must be revised to stay statistically reliable This study was carried out to estimate correct data based on outoregression and seasonal AutoRegressive Integrated Moving Average (ARIMA). As a result of verification through seasonal ARIMA, the longer the missed period is, the greater the error. Autoregression results in better verification results than seasonal ARIMA. Traffic data is affected by the present state mote than past patterns. However. autoregression can be applied only to the cases where data include similar neighborhood patterns and even in this case. the data cannot be corrected when data are missing due to low qualify or errors Therefore, these data shoo)d be corrected using past patterns and seasonal ARIMA when the missing data occurs in short periods.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.2
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• pp.149-166
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• 2006

The purpose of this study is to produce time-distance cartograms based on the various Korean transportation networks, and to analyze the spatial structure of time-distance accessibilities. For the purpose this study attempts to develop continuous area cartogram by utilizing Wolf's algorithm for creating contiguous cartogram in ArcGIS 9. The absolute physical space was transformed to the functional space indexed by time-distances along various transportation networks in Korea. We examined the differences in the time-distance accessibilities among transportation networks. This study makes a comparison between the spatial structure of time-distance accessibility of KTX network with them of existing railroad network, as well as with them of road network. In order to clarify the spatial structures of time-distance accessibilities, we restructured them on the time-distance circular diagrams and performing Multi-Dimensional Scaling analysis. Overall structure of time-distance accessibilities shows similar patterns: The time distances are shrinked a lot along the Seoul-Busan axis, while coastal parts, in particular the eastern part of the county, are shrinked relatively little via all transportation networks. The Road network affects significantly on the accessibilities of cities in Gangwon-do and Gyeonggi-do, while railway network affects on the accessibilities of cities in Jeolla-do and Gyeongsang-do in general. When we compared the time-distance accessibilities based on the 5 largest cities, Seoul appears as the most accessible city from/to all other cities in Korea. We can also find significant changes in the time-distance accessibility between KTX network and existing railroad network. Cities along the KTX network, in particular cities which has KTX stops, improved significantly in time-distance accessibilities.

• Spatial Information Research
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• v.19 no.3
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• pp.63-72
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• 2011

Urban space structure tends to have a significant change in accordance with maintenance of urban infrastructure such as a traffic route. For this reason, quantitative analysis has been needed to establish spatial distribution and location patterns by considering change of both road accessibility and urban infrastructure level, which can have the most pervasive influence in urban development process. Therefore, this paper aims to analyze spatio-temporal urban morphology through considering distribution patterns of road among transportation infrastructures, population, and spatial structure of metropolitan areas, focusing on Seoul where population growth and the size of urban area have been dramatically increased. For this, we firstly developed and constructed time-series GIS database by using satellite images and topographic maps of the last 70 years to analyze variables which affect urban growth and transportation. In particular, we analyzed the transform of the system of the street by Space Syntax which is able to grasp hierarchical spatial structure through visibility of space and spatial cognition in terms of accessibility. What's more, we analyzed and visualized the relationship urban morphology and road according the regions of Seoul through IPA(Importance Performance Analysis). In terms of the integration land-use and transportation, Space Syntax approach is expected to contribute to efficient urban planning through understanding the influence which various transportation phenomena has an effect on urban development patterns.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.155-168
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• 2018

In this study, we studied the directional pattern of entering the intersection from the intersection upstream link prior to predicting short future (such as 5 or 10 minutes) intersection direction traffic volume on the interrupted flow, and examined the possibility of traffic volume prediction using traffic assignment model. The analysis method of this study is to investigate the similarity of patterns by performing cluster analysis with the ratio of traffic volume by intersection direction divided by 2 hours using taxi DTG (Digital Tachograph) data (1 week). Also, for linking with the result of the traffic assignment model, this study compares the impact area of 5 minutes or 10 minutes from the center of the intersection with the analysis result of taxi DTG data. To do this, we have developed an algorithm to set the impact area of intersection, using the taxi DTG data and traffic assignment model. As a result of the analysis, the intersection entry pattern of the taxi is grouped into 12, and the Cubic Clustering Criterion indicating the confidence level of clustering is 6.92. As a result of correlation analysis with the impact area of the traffic assignment model, the correlation coefficient for the impact area of 5 minutes was analyzed as 0.86, and significant results were obtained. However, it was analyzed that the correlation coefficient is slightly lowered to 0.69 in the impact area of 10 minutes from the center of the intersection, but this was due to insufficient accuracy of O/D (Origin/Destination) travel and network data. In future, if accuracy of traffic network and accuracy of O/D traffic by time are improved, it is expected that it will be able to utilize traffic volume data calculated from traffic assignment model when controlling traffic signals at intersections.