• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.2
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• pp.1-12
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• 2008

Recently, the roll of bus transit is critical more than before because of the dramatical increase in congestions and oil prices, but bus companies seriously encounter into vicious circle situation such as decrease in passenger demand, income reduction, and revenue deterioration. To tackle this, major metropolitan cities, Seoul, Busan, DaeGu, etc. have introduced a semi-public system to reinforce public function of bus. However, it was resulted in side effects that the main board of bus company did not control theirselves voluntarily, and the management and control of public sectors on bus become very important elements. In this research, the types, limitations, and development of operation-management items, and a methodology for analysis, and changes in those trends are addressed under semi-public system using APTS data. Conclusively, this study could be one of the useful application results and alternatives for the operation-management policy of bus transit-related agencies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.82-96
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• 2020

The Demand Responsive Transit (DRT) system is the flexible public transport service that determines the route and schedule of the service vehicles according to users' requests. With increasing importance of public transport systems in urban areas, the development of stable and fast routing algorithms for DRT has become the goal of many researches over the past decades. In this study, a new heuristic method is proposed to generate fast and efficient routes for multiple vehicles using demand clustering and destination demand priority searching method considering the imbalance of users' origin and destination demands. The proposed algorithm is tested in various demand distribution scenarios including random, concentration and directed cases. The result shows that the proposed method reduce the drop of service ratio due to an increase in demand density and save computation time compared to other algorithms. In addition, compared to other clustering-based algorithms, the walking cost of the passengers is significantly reduced, but the detour time and in-vehicle travel time of the passenger is increased due to the detour burden.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1426-1440
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• 2008

In Korea, the concentration for the use of urban railroads is comparatively high during peak hours. In case of road traffic, overcrowdness leads the increase of total travel time and cost naturally but this does not happen in railroad systems because of fixed operational interval. Thus, passenger's disutility is generated physically and mentally from congestion increment. The increase of railroad capacity from new transit lines and expansion of existed lines contributes traveler's comfort benefits to rising. However, present evaluation guidelines for feasibility studies of road and railroad projects do not include any valuation methodology about passenger's comfort benefits. Therefore, in this research, various factors affecting comfort benefits are reviewed and stated preference survey is performed in order to estimate traveler's comfort benefits for congestion reduction. In addition, willingness to pay for congestion avoidance is calculated from that stated preference survey based on Tobit Model. As a result, detailed unit for willingness to pay according to congestion reduction is proposed in this study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.1-17
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• 2021

Identifying the exact train and the type of train boarded by passengers is practically cumbersome. Previous studies identified the trains boarded by each passenger by matching the Automated Fare Collection (AFC) data and the train schedule diagram. However, this approach has been shown to be inefficient as the exact train boarded by a considerable number of passengers cannot be accurately determined. In this study, we demonstrate that the AFC data - diagram matching technique could not estimate 28% of the train type selected by passengers using the Seoul Metro line no.9. To obtain more accurate results, this paper developed a two-step method for estimating the train type boarded by passengers by applying the AFC data - diagram matching method followed by a mixture distribution analysis. As a result of the analysis, we derived reasonable express train use/non-use passenger classification points based on 298 origin-destination pairs that satisfied the verification criteria of this study.

• 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.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.217-228
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• 2021

After the integrated fare system has been applied, public transportation and transfer traffic increased. As a result, transfer passengers must be considered in the operation of the bus. Although previous studies have limitations due to utilizing deterministic mathematical models, which fails to reflect the stochastic movements of passengers and buses, in this study, a more realistic bus stop micro-simulation model is proposed. Based on the proposed simulation model, we represent the relationship between bus arrival interval and passenger wait time as a regression model and empirically show the differences between the cases with and without transfer passengers. Also, we propose a method converting passenger waiting time to cost and find optimal bus arrival interval based on the converted cost. It is expected the proposed method enables bottom-up decision making reflecting practical situation.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.149-159
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• 2012

The evaluation of public transit service quality is more complicated than evaluating other aspects of transportation service. Although various measures of effectiveness [MOEs] for transit service have been studied and applied, a more comprehensive and accurate MOE is still required. In the past, either data from user surveys or the experience of bus agency administrators and/or engineers used to measure the quality of service. However, recently, with reliable and accurate real time data from BMS(Bus Management System) and BIS(Bus Information System), more reliable and accurate MOEs are available. This study develops a service evaluation model from users' perspectives, which is based on user' cost models that consider passenger access time, riding time, waiting time, and discomfort due to in-vehicle overcrowding, violation of traffic laws, and accident rate. For validating proposed model, data from the BMS and transit-fare cards (T-Money Card) for Seoul's No. 472 main bus line were used. Models developed in this study provided reliable results.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.379-395
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• 2006

The purpose of this study is to analyze the spatial characteristics of travel patterns and travel behaviors of transit users in the Metropolitan Seoul area. We apply the data mining techniques to explore the travel patterns of transit users from the T-money card database which has been produced over 10,000,000 transaction records per day. The database contains the information of locations and times of origin, transfer, and destination points for each transaction as well as the informations of transit modes taken via the transaction. We develop an data mining algorithm to explore traversal patterns from the enormous information. The algorithm determines the travel sequences of each passenger, and produce the volumes of support on each points (stops) of transportation networks in the Metropolitan Seoul area. In order to visualize the spatial patterns of travel demands for transit systems we apply GIS techniques, and attempt to investigate the spatial characteristics of travel patterns and travel demand. Subway stops located in the Gangnam area appear the highest peak for the travel origin and destination, while the CBD in the Gangbuk stands at the second position. Two or three sub-peaks appear at the densely populated residential areas developed as the high-rise apartment complex. Subway stations located along the Subway Line 2, especially from Guro to Samsung receive heavy travel demand (total support), while bus stops located at the CBD in the Gangbuk stands the highest travel demand by bus.

• Spatial Information Research
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• v.19 no.4
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• pp.11-20
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• 2011

In accordance with low carbon and green growth paradigm, a subway is one of major public transit systems for resolving traffic congestion and decreasing traffic accidents. In addition, as subway networks expand, passengers' travel pattern in the subway network change and consequently affect the urban structure. Generally, new subway route has been planned and developed, mainly considering a travel demand forecast. However, it is desired to conduct an empirical analysis on the forecast model regarding change of travel accessibility and passenger demand pattern according to new subway line. Therefore, in this paper, an alternative method, developed based upon a spatial syntax model, is proposed for evaluating new subway route in terms of passenger's mobility and network accessibility. In a case study, we constructed subway network data, mainly targeting the no 9 subway line opened in 2009. With an axial-map analysis, we calculated spatial characteristics to describe topological movement interface. We then analyzed actual modal shift and change on demand of passengers through the number of subway passenger between subway stations and the number of passenger according to comparative bus line from Smart Card to validate suggested methods. Results show that the proposed method provides quantitative means of visualizing passenger flow in subway route planning and of analyzing the time-space characteristics of network. Also, it is expected that the proposed method can be utilized for predicting a passengers' pattern and its impact on public transportation.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1321-1326
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• 2011

THE RAILWAY VEHICLE IS CONSISTS OF CARBODY, BOGIE AND WHEELSETS, EACH OF COMPONENTS IS CONNECTED WITH RIGID MASS, SPRING AND DAMPER. EACH OF COMPONENTS HAS TRANSLATION MOTIONS OF LONGITUDINAL (X AXIS), LATERAL (Y AXIS) AND VERTICAL (Z AXIS) DIRECTIONS, ROTATION MOTIONS OF X, Y, Z AXIS WHICH ARE NAMED ROLLING, PITCHING AND YAWING. THE VIBRATION MODE OF RAILWAY VEHICLE IS DIFFICULT TO FIND THE CHARACTERISTICS OF MOTION DURING THE OPERATION ON THE TRACK BECAUSE THESE HAPPEN TO INDEPENDENCE OR DUPLICATION MOTION CAUSED BY VEHICLE, WHEEL/RAIL AND TRACK IRREGULARITY ETC. IT IS NAMED AN ABNORMAL VIBRATION THAT THE VIBRATION, WHICH WAS PASSED THE PRIMARY AND SECONDARY SUSPENSION, IS AFFECTED TO THE PASSENGER WITHOUT DAMPING. THIS PAPER DESCRIBES AN EXPERIENCE EVALUATION TO FIND THE CAUSE OF AN ABNORMAL VIBRATION WHICH WAS HAPPEN AT OPERATING SPEED 60KPH ZONE DURING THE MAINLINE TEST.