• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.38-39
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• 2010

수도권 대중교통 이용자는 2004년 서울시의 대중교통 체계 개편에 따라 교통 카드를 사용하여 버스와 지하철을 이용하게 되었다. 교통 카드를 사용하는 각 승객의 승차와 하차에 관한 데이터가 하나의 트랜잭션으로 구성되고, 하루 천만 건 이상의 트랜잭션들로 구성된 대용량 교통카드 트랜잭션 데이터베이스가 만들어지고 있다. 대중교통을 이용하는 승객들의 승차와 하차에 관한 여러 정보를 담고 있는 교통카드 트랜잭션 데이터베이스에서 유용한 패턴이나 정보를 탐사해내는 연구가 계속 진행되고 있다. 이런 연구 결과는 수도권 대중교통 정책을 입안하는데 중요한 기초 자료가 되고 수도권 승객들에게 대중교통을 보다 잘 이용할 수 있는 정보로 제공된다. 교통카드 이용률은 2006년 79.5%, 2007년 80.3%, 2008년 81.6%로 점차적으로 증가하고 있다. 대용량의 교통카드 트랜잭션 데이터베이스에 대한 연구를 살펴보면 하루 동안의 교통카드 트랜잭션 데이터베이스에서 순차 패턴을 탐사하는 알고리즘을 연구하였고[1], 승객들의 통행 패턴에 대한 분석연구를 확장하여 일 년에 하루씩 2004년에서 2006년까지 3일간의 교통카드 트랜잭션 데이터베이스로부터 승객 시퀀스의 평균 정류장 개수와 환승 횟수 등을 연도별로 비교하였다[2]. 수도권 지하철 시스템의 특성에 관한 연구로는 네트워크 구조 분석이 있었고[3], 승객의 기종점 통행 행렬(Origin-Destination trip matrix)에 의한 승객 흐름의 분포가 멱함수 법칙(power law)임을 보여주는 연구가 있었고[4], 지하철 교통망에서 모든 링크상의 승객들의 흐름을 찾아내는 연구가 있었다[5]. 본 논문에서는 교통카드 트랜잭션 데이터베이스에서 지하철 승객들의 통근 패턴을 탐사해내는 방법을 연구하였다. 수도권 지하철 네트워크에 대한 정보를 입력하고 하루치의 교통카드 트랜잭션 데이터베이스에 연구된 방법을 적용하여 8가지 통근 패턴들을 탐사해내고 분석하였다. 탐사된 패턴들 중에서 많은 승객들이 지지하는 출퇴근 패턴에 대해서는 시간대별로 승객수를 그래프로 보여주었다.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.91-100
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• 2010

To understand the trip patterns of subway passengers is very important to making plans for an efficient subway system. Accordingly, there have been studies on mining and classifying useful patterns from large smart card transaction databases of the Metropolitan Seoul subway system. In this paper, we define a new classification of subway trip patterns and devise a classification algorithm for eleven trip patterns of the subway users from smart card transaction databases which have been produced about ten million transactions daily. We have implemented the algorithm and then applied it to one-day transaction database to classify the trip patterns of subway passengers. We have focused on the analysis of significant patterns such as round-trip patterns, commuter patterns, and unexpected interesting patterns. The distribution of the number of passengers in each trip pattern is plotted by the get-on time and get-off time of subway transactions, which illustrates the characteristics of the significant patterns.

• Journal of the Economic Geographical Society of Korea
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• v.18 no.4
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• pp.539-555
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• 2015

This study proposes the methodology for measuring the time-distance accessibility on the Seoul bus system based on the T-card transaction databases and analyzes the results. T-card transaction databases contain the time/space information of each passenger's locations and times of the departure, transfers, and destination. We introduce the bus network graph and develop the algorithms for time-distance accessibility measurement. We account the average speed based on each passenger's get-in and getoff information in the T-card data as well as the average transfer time from the trip chain transactions. Employing the modified Floyd APSP algorithm, the shortest time distance between each pair of bus stops has been accounted. The graph-theoretic nodal accessibility has been given by the sum of the inverse time distance to all other nodes on the network. The results and spatial patterns are analyzed. This study is the first attempt to measure the time-distance accessibility for such a large transport network as the Seoul bus system consists of 34,934 bus stops on the 600 bus routes, and each bus route can have different properties in terms of speed limit, number of lanes, and traffic signal systems, and thus has great significance in the accessibility measurement studies.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.316-323
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• 2010

We propose a method to find flows of transit users in the subway transportation network of the metropolitan Seoul and analyze the passenger flows on some central links of the network. The transportation network consists of vertices for subway stops, edges for links between two adjacent subway stops, and flows on the edges' Each subway transit user makes a passenger flow along edges of the shortest path from the origin stop to the destination stop in his trip. In this paper, we have developed a new algorithm to find the passenger flow of each link in the subway network from a large trip-transaction database of subway transit users. We have applied the algorithm to find the passenger flows from one day database of about 5 million transactions by the subway transit users. As results of the experiments, the travel behavior on 4 central subway links is analyzed in passenger flows and top 10 flows among all subway links are explained in a table.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.1
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• pp.20-33
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• 2018

Population distribution in urban space varies with transportation flow changing along time of day. Transportation flow is directly affected by the activities of urbanites and the distribution of related facilities, since the flow is the result of moving to the point where the facilities associated with their activities are located. It is thus necessary to analyze the spatio-temporal characteristics of the urban population distribution by integrating the distribution of activity spaces related to the daily life of urbanites and the flow of transportation. The purpose of this study is to analyze the population distribution in urban space with daily and weekly time bases using the building database and T-card database in the city of Seoul, which is rich in information on land use and transportation flow. For a time-based analysis that is difficult to grasp by general statistical techniques, a four-dimensional visualization method combining time and space using a Java program is devised. Dynamic visualization in the four-dimensional space and time allows intuitive analysis and makes it possible to understand more effectively the spatio-temporal characteristics of population distribution. For this purpose, buildings are classified into three activity groups: residential, working, and commercial according to their purpose, and the number of passengers traveling to and from each stop site of bus and subway networks in the T-card database for one week is calculated in one-minute increments, Visualizing these and integrating transportation and land use, we analyze spatio-temporal characteristics of the population distribution in Seoul. As a result, it is found that the population distribution of Seoul displays distinct spatio-temporal characteristics according to land use. In particular, there is a clear difference in the population distribution pattern along the time axis according to the mixed aspects of working, commercial, and residential activities. The results of this study can be very useful for transportation and location planning of city facilities.

• 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 Korean Regional Science Association
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• v.33 no.1
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• pp.29-41
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• 2017

This study proposes an integrated accessibility measurement algorithm, which is applied to the Seoul Metropolitan public transportation system consisting of bus and subway networks, and analyzes the result. We construct a public transportation network graph linking bus-subway networks and take the time distance as the link weight in the graph. We develop a time-distance algorithm to measure the time distance between each pair of transit stations based on the T-card transaction database. The average travel time between nodes has been computed via the shortest-path algorithm applied to the time-distance matrix, which is obtained from the average speed of each transit route in the T-card transaction database. Here the walking time between nodes is also taken into account if walking is involved. The integrated time-distance accessibility of each node in the Seoul Metropolitan public transportation system has been computed from the T-card data of 2013. We make a comparison between the results and those of the bus system and of the subway system, and analyze the spatial patterns. This study is the first attempt to measure the integrated time-distance accessibility for the Seoul Metropolitan public transportation system consisting of 16,277 nodes with 600 bus routes and 16 subway lines.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.2
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• pp.116-128
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• 2011

Some subway passengers may want to have their fresh vegetables purchased through internet at a service facility within the subway station of the Metropolitan Seoul subway system on the way to home, which raises further questions about which stations are chosen to locate service facilities and how many passengers can use the facilities. This problem is well known as the pickup problem, and it can be solved on a traffic network with traffic flows which should be identified from origin stations to destination stations. Since flows of the subway passengers can be found from the smart card transaction database of the Metropolitan Seoul smart card system, the pickup problem in the Metropolitan Seoul subway system is to select subway stations for the service facilities such that captured passenger flows are maximized. In this paper, we have formulated a model of the pickup problem on the Metropolitan Seoul subway system with subway passenger flows, and have proposed a fast heuristic algorithm to select pickup stations which can capture the most passenger flows in each step from an origin-destination matrix which represents the passenger flows. We have applied the heuristic algorithm to select the pickup stations from a large volume of traffic network, the Metropolitan Seoul subway system, with about 400 subway stations and five millions passenger transactions daily. We have obtained not only the experimental results in fast response time, but also displayed the top 10 pickup stations in a subway guide map. In addition, we have shown that the resulting solution is nearly optimal by a few more supplementary experiments.

• Digital Contents
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• no.2 s.153
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• pp.70-73
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• 2006

복용방법 및 용량, 부작용이나 주의사항 등의 정보가 모두 담겨 있는 약병. 출고부터 물류센터, 매장에 이르기까지 재고와 출납현황이 모두 실시간으로 추적되는 물류시스템. 생산지와 가공, 유통 이력이 모두 기록되어 있는 농산물. 그리고 우리가 매일 쓰고 있는 교통카드까지, RFID는 미래에 실현될 막연한 개념이 아니라 이미 광범위한 분야에서 적용되고 있는 기술로 우리 곁에 다가왔다. 본고에서는 세계 최초의 모바일 RFID 게임인 <사립탐정>의 사례를 통해 RFID와 유비쿼터스 핵심 개념의 실체에 대해 살펴보고,RFID·USN 엔터테인먼트 콘텐츠의 발전방향에 대해 알아본다.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.158-172
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• 2017

This study analyzes the time-space variability for the weekly passenger flow of the Seoul Subway system based on the dynamic visualization methods. For the purpose, we utilize one-week T-card transaction databases. By applying data mining algorithms, we extract passenger data for edge flows, on/off passengers at each subway station per minute interval time. It is practically intractable to analyze such spatio-temporal passenger flows by general statistical techniques. We employ dynamic visualization methods to analyze intuitively and to grasp effectively characteristics of the diurnal passenger flows on the Seoul Metropolitan Subway system during one week. As the result, we found that substantial differences exist on the spatio-temporal distribution patterns among days as well as between weekdays and weekend. We also investigates the time-space variability among eight major centers, and we found wide differences in their spatio-temporal distribution patterns.