• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.31-38
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• 2009

The objective of this paper is to propose the bus information system that provides bus passenger number. Recently, we use a bus conveniently through introduction of bus information system offering location-based information. However, we need additional information for decision making in order to use a bus comfortably. To do this, first, we analyzed the needs of providing passenger number; second, we adopted GPS and RFID type's transportation card to get location and passenger number. Finally, we implemented the system displaying that information by three types, and tested it. Our proposed system has advantages to use a bus comfortably and to manage a bus efficiently by providing bus passenger number which is the important element for decision making as well as location based information provided by existing bus information systems.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.849-851
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• 2016

본 논문은 버스 탑승 인원을 혼잡 정도로 제공하는 버스 정보 시스템의 구현을 목적으로 한다. 최근 버스 정보 시스템의 도입을 통하여 버스 이용자에게 다양한 위치 기반 정보를 제공함으로써 편의성을 제공하고 있다. 그러나 쾌적한 버스를 이용하기 위하여 버스 선택을 위한 의사결정에 필요한 정보의 제공이 요구된다. 이를 위하여 승차인원 정보 제공의 필요성을 분석하고 라즈베리파이에 GPS모듈과 적외선 센서를 이용하여 통신함으로써, 탑승인원 정보를 수집하고 더불어 가공하여 버스 내에 탑승 인원 혼잡 정도를 스마트폰을 통하여 정보를 제공할 수 있도록 구현하였다. 제안한 시스템은 버스 위치 기반 관련 정보와 버스 이용객의 의사 결정 을 위한 주요한 요소인 승차인원 정보를 제공함으로써 쾌적한 버스이용과 효율적인 버스 관리의 장점을 제공한다.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.111-128
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• 2019

Subways are eco-friendly public transportation that can transport large numbers of passengers safely and quickly. It is necessary to predict the accurate number of passengers in order to increase public interest in subway. This study groups stations on Lines 1 to 9 of the Seoul Metropolitan Subway using clustering analysis. We propose one final prediction model for all stations and three optimal prediction models for each cluster. We found three groups of stations out of 294 total subway stations. The Group 1 area is industrial and commercial, the Group 2 ares is residential and commercial, and the Group 3 area is residential districts. Various data mining techniques were conducted for each group, as well as driving some influential factors on demand prediction. We use our model to predict the number of passengers for 8 new stations which are part of the 3rd extension plan of Seoul metro line 9 opened in October 2018. The estimated average number of passengers per hour is from 241 to 452 and the estimated maximum number of passengers per hour is from 969 to 1515. We believe our analysis can help improve the efficiency of public transportation policy.

• Proceedings of the KSR Conference
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• 2006.05b
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• pp.21-26
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• 2006

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.23-24
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• 2011

본 논문에서는 승객 수송수요 반영 단계에서는 역별 승하차인원, 시간대별 재차인원 등 수송수요에 반영할 기준을 설정하여 수송력과 승차인원의 기준을 판단하고, 열차운행계획 수립 단계에서는 운행구간, 선로용량, 선로조건 등 제약조건과 적정수송력에 맞는 운행계획을 수립하고, 마지막 단계에서 경제성, 능률성, 합리성 등을 감안한 운용효율 향상을 위한 열차 DIA를 작성하고자 한다. 또한 통계적 분석절차에 따라 재차인원과 운행횟수를 각각의 독립변수와 종속변수로 산정하여 두 변수간의 상관관계를 확인한 후 회귀분석을 통해 얻은 회귀식을 실제열차운행 횟수와 비교하여 최적의 열차운행횟수를 산정하였으며 회귀식의 유효성 검증을 통해 열차운행 환경변화에 신속하게 대응할 수 있는 유연한 시스템을 구축한 후 서울도시철도공사 실용 Dia에 적용하여 유효성을 검토하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.1-9
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• 2012

This study proposed a method to determine the number and location of bus information terminals (BIT), which is a device to provide passengers with bus arrival time at bus stops in a Bus Information System (BIS). In low-density area, it is not efficient to survey bus demands such as the number of passengers at all bus stops due to time and cost. This kind of a survey would, however, competently cover all bus stops if performed inside the bus. The number of riding-on and -off passengers is observed for every bus stop, and this data collection is repeated over all day. Data obtained from the survey are aggregated each bus stop. This study defines Utility Index (UI), an aggregate each bus stop. Bus stops are ranked according to UI and determined for a BIT within budget limitation. As a case study, a bus line in Jeju island, Korea, was dealt with. This case showed that the more aggregate the better data quality. This study is expected to contribute to solving a location problem of BITs in a BIS.

• Journal of the Korean Society for Railway
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• v.16 no.6
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• pp.482-491
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• 2013

Current metro tickets are categorized into transportation cards and monthly season tickets, which offer limited consumer choices. A metro fare system should be introduced based on the diversity of customer demand. Thus, this study's objective is that the metro fare system in Korea should be efficiently operated by analyzing a variety of metro fare systems used in major cities of other countries. In addition, this study proposed the following metro fare systems, one day pass, which is generally used in other countries in a bid to promote public transportation, reduce costs, and increase revenue. A commuting ticket system to increase the demand from cars to subways, and special discounts & a round-trip ticket system for round-trip travelers in case that demand is low was compared with the high supply on the Gyeongchun-line.

• Journal of the Korean Society for Railway
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• v.18 no.2
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• pp.166-174
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• 2015

A direct demand model requires relatively little analysis time and incurs a low cost. It is also known to be useful for the preliminary screening of promising configurations or concepts. This study reviews direct demand models of 12 existing urban railways using demographic data based on a block group level which is approximately 1/24 of a traditional zone area. However, direct demand models are limited. Therefore, a new approach is suggested. The proposed method is based on a field study and an empirical analysis. The study finds factors that affect ridership at the station level. As a case study, the proposed approach is tested using 54 light railway transit stations. The results of this empirical study demonstrate its applicability to improve the error rates of the predicted ridership at the station level.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.67-77
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• 2022

An automatic freeway bus-only lane enforcement system was developed and assessed in a real-world environment. Observation of a bus-only lane on the Youngdong freeway, South Korea, revealed that approximately 99% of the vehicles violated the high-occupancy vehicle (HOV) lane regulation. However, the current enforcement by the police not only exhibits a low enforcement rate, but also induces unnecessary safety and delay concerns. Since vehicles with six passengers or higher are permitted to enter freeway bus-only lanes, identifying the number of passengers in a vehicle is a core technology required for a freeway bus-only lane enforcement system. To that end, infrared cameras and the You Only Look Once (YOLOv5) deep learning algorithm were utilized. For assessment of the performance of the developed system, two environments, including a controlled test-bed and a real-world freeway, were used. As a result, the performances under the test-bed and the real-world environments exhibited 7% and 8% errors, respectively, indicating satisfactory outcomes. The developed system would contribute to an efficient freeway bus-only lane operations as well as eliminate safety and delay concerns caused by the current manual enforcement procedures.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.3
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• pp.15-27
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• 2017

In general, increasing train dwell time leads to increasing train service frequency, and it in turn contributes to increasing the congestion level of train and platform. Therefore, the studies on train dwell time have received growing attention in the perspective of scheduling train operation. This study develops a prediction model of train dwell time to enable train operators to mitigate platform congestion by metering passenger inflow at platform gate with respect to platform congestion levels in real-time. To estimate the prediction model, three types of independent variables were applied: number of passengers to get into train, number of passengers to get out of trains, and train weights, which are collectable in real-time. The explanatory power of the estimated model was 0.809, and all of the dependent variables were statistically significant at the 99%. As a result, this model can be available for the basis of on-time train service through platform gate metering, which is a strategy to manage passenger inflow at the platform.