• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.233-243
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• 2008

Recognition for the importance and roles of public transportation is increasing because of traffic problems in many cities. In spite of this paradigm change, previous researches related with public transportation trip assignment have limits in some aspects. Especially, in case of multimodal public transportation networks, many characters should be considered such as transfers. operational time schedules, waiting time and travel cost. After metropolitan integrated transfer discount system was carried out, transfer trips are increasing among traffic modes and this takes the variation of users' route choices. Moreover, the advent of high-technology public transportation card called smart card, public transportation users' travel information can be recorded automatically and this gives many researchers new analytical methodology for multimodal public transportation networks. In this paper, it is suggested that the methodology for establishment of brand new multimodal public transportation networks based on computer programming methods using transportation card data. First, we propose the building method of integrated transportation networks based on bus and urban railroad stations in order to make full use of travel information from transportation card data. Second, it is offered how to connect the broken transfer links by computer-based programming techniques. This is very helpful to solve the transfer problems that existing transportation networks have. Lastly, we give the methodology for users' paths finding and network establishment among multi-modes in multimodal public transportation networks. By using proposed methodology in this research, it becomes easy to build multimodal public transportation networks with existing bus and urban railroad station coordinates. Also, without extra works including transfer links connection, it is possible to make large-scaled multimodal public transportation networks. In the end, this study can contribute to solve users' paths finding problem among multi-modes which is regarded as an unsolved issue in existing transportation networks.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.922-924
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• 2002

현재 IC카드는 통신, 금융, 교통 등의 여러 응용 서비스에서 널리 사용되고 있는데, 계속적인 하드웨어 기술의 발전으로 인한 메모리 증가, CPU 성능 향상과, 통합된 정보 가전을 위한 다양한 형태의 네트워크 연결 인터페이스 구축 노력이 다중 응용 프로그램(Multi-Application) 사용 요구 및 개방형 운영체제(Open-platform Operating System)와 맞물려 도약적인 기술 발전을 이루고 있다. 본 고에서는 널리 사용되고 있으며 향후 시장성이 가장 클 것으로 예측되는 자바 카드 플랫폼 탑재 IC카드의 기술 현황을 H/W 및 S/W측면에서 살펴보고, 자바 카드 기술의 발전 동향을 조망하고자 한다.

• Transportation Technology and Policy
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• v.2 no.2
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• pp.113-126
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• 2005

• Journal of Korean Electronics
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• v.26 no.12
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• pp.24-24
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• 2006

• Transportation Technology and Policy
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• v.4 no.4
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• pp.31-58
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• 2007

• Railway Journal
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• v.13 no.4
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• pp.30-32
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• 2010

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.49-63
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• 2019

Crowdedness management at subway platforms is essential to improve services, including the prevention of train delays and ensuring passenger safety. Establishing effective crowdedness mitigation measures for platforms requires accurate estimation of the congestion level. There are temporal and spatial constraints since crowdedness on subway platforms is assessed at certain locations every 1-2 years by hand counting. However, smart cards generate real-time big data 24 hours a day and could be used in estimating congestion. This study proposes a model based on data from transit cards to estimate crowdedness dynamically. Crowdedness was defined as demand, which can be translated into passengers dynamically moving along a subway network. The trajectory of an individual passenger can be identified through this model. Passenger flow that concentrates or disperses at a platform is also calculated every minute. Lastly, the platform congestion level is estimated based on effective waiting areas for each platform structure.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.391-398
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• 2022

The use rate of M-pass(transportation card for foreigners),developed and sold to provide convenience to foreign tourists, was only 0.0051 % of visitors to Seoul over the past five years. Even this poor sales fell to the 0.024 % level in 2020 due to COVID-19. The cause of the sluggish performance was that the Ministry of land, Transport and Maritime Affairs and the card issuer excluded transportation operating organizations, and problems such as poor public relation, irrationality in pricing, and limitied number of sales locations appeared. In order to solve this problem, the research result showed that business strategies such as the establishment of a digital marketing system, realistic pricing, and the establishment of a mobile sales system that fit the trend, as well as the development of new product that reflect the participation and opinions of all related organizations are necessary. It is expected that this study will not only provide convenience to foreign Seoul tourist in the age of Post Corona, but also help improve the management of subway operating organizations.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.623-634
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• 2013

In this study, we provide empirical evidence of whether a spatial correlation among mode choices at the TAZ(Traffic Analysis Zone) level exists based on transit smart card data observed in Seoul, Korea. The results show that the areas with a higher probability that passengers choose to take a bus are clustered and that those regions have fewer metro stations than bus stations. We also found that the spatial correlation turned out to be statistically meaningful and provided an opportunity for the potential use of the spatial correlation in modeling mode choices. A reliable spatial interaction would constitute valuable information for transportation agencies in terms of their route planning and scheduling based on the transit smart card data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.14-24
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• 2018

Pedestrian movement of passengers using smart card within stations can be divided into three types of activities - straight ride and alight, line transfer, and station transfer. Straight ride and alight is transfer activity for which the card terminal and embarking line are identical. In this case, straight ride occurs at the origin station and straight alight occurs at the destination station. Line transfer refers to activity in which the subway line embarked on by the passenger is different from that which is disembarked. Succinctly, line transfer is transfer at a middle station, rather than at origin or destination stations. Station transfer occurs when the card terminal line and embarking line are different. It appears when station transfer happens at the origin station as starting transfer, and at the destination station as destination transfer. In the case of Metropolitan smart card data, origin and destination station card terminal line number data is recorded, but subway line data does not exist. Consequently, transportation card data, as it exists, cannot adequately be used to analyze pedestrian movement as a whole in subway stations. This research uses the smart card data, with its constraints, to propose an analysis model for passenger pedestrian movement within subway stations. To achieve this, a path selection model is constructed, which links origin and destination stations, and then applied for analysis. Finally, a case study of the metropolitan subway is undertaken and pedestrian volume analyzed.