• Proceedings of the KSR Conference
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• 2003.10c
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• pp.236-246
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• 2003

This paper is implemented a control algorithm in order to be stable and minimized to entire train traffic system at delayed case. Signal ing system is described wi th algebraic equations given for train headway, Discrete-event simulation principles are reviewed and a demonstration block signaling model using the technique is implemented. Train congestion at station entrance for short headway operation is demonstrated and the propagation of delays along a platform of trains from any imposed delay to the leading train is also shown. A rail way signaling system is by nature a distributed operation with event triggered at discrete intervals. Although the train kinematic variables of position, velocity, and acceleration are continually changing, the changes are triggered when the trains pass over section boundaries and arrive at signals and route switches. This paper deals with linear-mode1ing, stability and optimal control for the traffic on such metro line of the model is reconstructed in order to adapt the circuits. This paper propose optimal control laws wi th state feedback ensuring the stability of the modeled system for circuits. Simulation results show the benefit to be expected from an efficient traffic control. The main results are summarized as follows: 1. In this paper we develop a linear model describing the traffic for both loop lines, two state space equations have been analyzed. The first one is adapted to the situation where a complete nominal time schedule is available while second one is adapted when only the nominal time interval between trains is known, in both cases we show the unstability of the traffic when the proceeding train is delayed following properties, - They are easily implemented at law cost on existing lines. - They ensure the exponetial stability of loop system. 2. These control laws have been tested on a traffic simulation software taking into the non-linearites and the physical constraints on a metro line. By means of simulation, the efficiency of the proposed optimal control laws are shown.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.2
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• pp.36-49
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• 2016

A subway system is one of the major transportation modes at a metropolitan area. When it meets the other lines, the metro station, so-called transferring station, is usually threatened by severe pedestrian congestion and safety issue of transit users including the transportation vulnerable. Although transportation planners forecast travel demand at the beginning, it is not easy to predict pedestrian flows precisely for a long term if land use plans have dramatically changed. Due to expensive costs, structural extension of metro stations is limited. Therefore, it requires efficient and technical improvements as meeting the demand of pedestrian and physical characteristics. In this study, the core mechanism of pedestrian movement-based simulation model was introduced and evacuation scenarios were analyzed with the developed model. As a result, the multiple optimal routes for unexpected events at the solid space of the multiple stories are easily searched through the simulator and in the case of Sadang Station, travel time can be reduced by 60% when the evacuation information and intuitive design are provided.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.679-686
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• 2008

There has been an increasing demand of introducing innovative public transport modes meriting high flexibilities of a bus mode along with on-time accuracy and quality environment-friendliness of a rail mode, as it is considered to significantly contribute to reducing huge social expenditures on the traffic congestion and environmental pollution agenda, and to be an alternative solution to better the urban transport problems. In order to comply with the need, Seoul Municipal Government has recently decided to build up GRT system of a new concept in Nangok area in Seoul, the first in its kind in Korea. The concession has been awarded to Seoul Metro. This thesis will study and benchmark similar systems abroad under operation, and further review necessary requirements overall which would secure full readiness for the operation of Nangok GRT system.

• Advanced Industrial SCIence
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• v.2 no.4
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• pp.11-16
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• 2023

The subway is a means of public transportation that plays an important role in the transportation system of modern cities. However, congestion often occurs due to sudden breakdowns and system outages, causing inconvenience. Therefore, in this paper, we conducted a study on failure prediction and prevention using machine learning to efficiently operate the subway system. Using UC Irvine's MetroPT-3 dataset, we built a subway breakdown prediction model using logistic regression. The model predicted the non-failure state with a high accuracy of 0.991. However, precision and recall are relatively low, suggesting the possibility of error in failure prediction. The ROC_AUC value is 0.901, indicating that the model can classify better than random guessing. The constructed model is useful for stable operation of the subway system, but additional research is needed to improve performance. Therefore, in the future, if there is a lot of learning data and the data is well purified, failure can be prevented by pre-inspection through prediction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.3220-3226
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• 2011

In order to monitor internal risk factors such as fire, terror, etc. on the subway station, the surveillance systems using CCTV and various kinds of sensors have been implemented and recently, introduction of surveillance systems using an advanced IT technology, sensor network technology is tried on several areas. Since 2007, Korean government has made an effort to develop the intelligent surveillance and monitoring system, which can monitor fire, intrusion, passenger congestion, health-state of structure, etc., by using wireless sensor network technology and intelligent video analytic technique. For that purpose, this study carried out field wireless communication environment test on Chungmuro Station of Seoul Metro on the basis of ZigBee that is considered as a representative wireless sensor network before field application of the intelligent integrated surveillance system being developed, arranged and analyzed and ZigBee based wireless communication environment test results on the platform and waiting room of Chungmuro Station on this paper. Results of wireless spectrum analysis on the platform and waiting room showed that there is no radio frequency overlapped with that of ZigBee based sensor network and no frequency interference with adjacent frequencies separated 10MHz or more. As results of wireless data transmission test using ZigBee showed that data transmission is influenced by multi-path fading effect from the number and flow rate of passengers on the platform or the waiting room rather than effects from entrance and exit of the train to/from the platform, it should be considered when implementing the intelligent integrated surveillance system on the station.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.189-210
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• 2022

Cities around the world have paid attention to public transportation as an alternative to reducing traffic congestion caused by automobile usage, excessive energy consumption, and environmental pollution. This study measures accessibility to subway stations in Seoul using a supply-demand-based accessibility technique. Then, the impacts were analyzed through land prices by use and segment. As a result of analysis using the multilevel hedonic price models, accessibility considering both supply and demand for the subway had a positive effect on both residential and non-residential land prices. The effect was stronger for residential than for non-residential. Further, among the accessibility measured by the three functions, the accessibility by the Exponential function was most suitable for the residential land price, and the accessibility measured by the Power function for the non-residential land price had the highest explanatory power. Also, looking at the impacts by land price segments, it was found that higher access to metro stations had the greatest positive impacts on the most expensive segment of residential and non-residential land prices. The results of this study can be applied not only to identify the impacts of public investment on neighborhoods, but also to support real estate valuation.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1009-1013
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• 2011

Seoul Metro Line 1 to 4 guests per day to 4.5 million people have been using the subway. This is close to the city population, 57 percent of people use the subway and found that 57 percent of people use the subway and found that this is close to the city population. Motor vehicle indoor air quality, especially of the major factors affecting is passenger's clothing, cosmetics, adhesives and formaldehyde by the action and so are able to keep. Enclosure 30ppm formaldehyde during prolonged exposure at concentrations above the nose, bronchial cough and a burning can cause symptoms. It is necessary to introduce an appropriate ventilation system. 1-4 Line Press in 2008, leaving the subway, and normally the train measured in room air quality. Measurements in 2005, $19.3{\sim}83{\mu}g/m^3$, 2008 Year ND ~ $61.7{\mu}g/m^3$ is. When congestion(rush hour) to temporarily increase the formaldehyde can result in a higher number. Automatic detection of formaldehyde and improve ventilation to a practical system, and it is necessary to chatneun. In research since 2006, Removal of formaldehyde were analyzed for the study. the passengers on the effects of formaldehyde in rush hour, the plan for increasing the ventilation through the analysis of various factors, such as electric vehicle practical ways to improve air quality have been studied.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.195-197
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• 2009

It is a proven fact with the opening of the Seoul metro line number 1 in 1974 traffic congestion on the roads has decreased and the efficiency of people transportation in general has greatly been enhanced in the downtown and surrounding areas of Seoul. Even today construction of new subway lines are under way and many more are being planned due to the easy access to stations, short waiting and average travel times, compared with personal vehicles, contributing to the efficiency of the public transportation systems that are linking the downtown areas and also the intercity systems in moving passengers during rush hour and times of special event. Since the labour costs of the train operator in any large city based subway system accounts for a major part of the operating costs per kilometer and to ensure cost efficient operations, especially during non-peak hours, it is necessary to implement an unmanned(auto-driven) subway system. In order to implement such a system it is imperative that the on-board and wayside signalling control systems be fully automated as well. Only through proper examination of safety procedures not only by the AUGT(Automated Urban Guided Transport)system but also by ail the international standards organizations involved can safely and stability be ensured.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.