• KIPS Transactions on Computer and Communication Systems
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• v.6 no.7
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• pp.297-306
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• 2017

Citizens want more accurate forecast information using Bus Information System. However, most bus information systems that use an average based short-term prediction algorithm include many errors because they do not consider the effects of the traffic flow, signal period, and halting time. In this paper, we try to improve the precision of forecast information by analyzing the influencing factors of the error, thereby making the convenience of the citizens. We analyzed the influence factors of the error using BIS data. It is shown in the analyzed data that the effects of the time characteristics and geographical conditions are mixed, and that effects on halting time and passes speed is different. Therefore, the halt time is constructed using Generalized Additive Model with explanatory variable such as hour, GPS coordinate and number of routes, and we used Hidden Markov Model to construct a pattern considering the influence of traffic flow on the unit section. As a result of the pattern construction, accurate real-time forecasting and long-term prediction of route travel time were possible. Finally, it is shown that this model is suitable for travel time prediction through statistical test between observed data and predicted data. As a result of this paper, we can provide more precise forecast information to the citizens, and we think that long-term forecasting can play an important role in decision making such as route scheduling.

• 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.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1612-1627
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• 2008

Dwelling time is one of the factors that influence in rail. Current research in dwelling time has been focusing on railways, the state of the research in high-speed rail's dwelling time is not complete. Dwelling time is consisted of time to open door, time to get into and out of vehicle and time of the departure it takes after the passenger's door was closed, it was affected by various factors such as congestion's degree in vehicle, the number of persons that get into and out of vehicle, congestion's degree in station. In order to analyze theses, we need data analysis such as the number of persons that get into and out of vehicle, congestion's degree in station, congestion's degree in vehicle, but the congestion's degree and passenger's distribution chart in vehicle is excluded in this research due to difficulty of gathering data, and thus we will develop forecasting models through high-speed rail's demand most affected by the dwelling time.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.147-156
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• 2006

Metropolitan Subway, tke volume of station, distance between station is short. when the demand is concentrated during moving peak periods, the Headway that than Line Headway in which Station Headway is applied to Station Capacity computation be. The factors to determine the Station Headway have a fixing Price of the machine and the Dwell time. Other factors aye decided already or fixing price but the Dwell time that change according to demand cause the biggest effect at Station Headway. After analyze constituents that influence to Station Headway in this study calculated correct Station Capacity drawing estimating dwell time model that change according to demand.

• Journal of Korean Society of Transportation
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• v.25 no.5
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• pp.111-122
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• 2007

This paper investigates the rail service patterns by train class. The emphasis in intercity rail planning is to more efficiently use of existing station facilities. Rail transit operations are affected by the system layout and ridership patterns and by work rules. Operations are also influenced by past practices and the institutional setting. Main factors to decide train service patterns are the location, socioeconomic characteristics, land use and travel demand of the station. In this context, the travel demand of intercity rail station is of crucial significance. Tests on a KTX case shows that train service frequency can be efficiently decreased in weekday to transport the same passenger demand. The work has shown many subjects that need further research including various factors influencing on train frequency. This study serves the railroad authorities in planning and determining business strategy in the increasingly competitive environment of regional rail transport.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.527-536
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• 2022

The purpose of this study is to predict changing traffic environments and related economic effects by reflecting the changed KTDB and socio-economic indicators pertaining to Mulgeum station, a general railway stop, when it is confirmed as a KTX stop. To analyze the data of this study, socioeconomic indicators and the general status of transportation facility operations were investigated with reference to related statistical data, centered on the country overall and on Yangsan city in particular. In addition, we investigated and referenced the railroad facility construction plan and train operation plan, which are national high-level plans related to land development and transportation network construction. Currently, there are only ITX trains (4 times/day) and Mugunghwa trains (29 times/day) that stop at Mulgeum station in Yangsan, meaning that passengers cannot use KTX trains in the Yangsan area. In particular, the need for a KTX stop at Mulgeum station has been continuously raised because train users in the Yangsan area have inconvenient transportation in that they must travel 40 minutes to Ulsan station or 30 minutes to Gupo station to use the KTX. As a result of analyzing railroad transportation demand that will change in the future as the KTX stop at Mulgeum station is confirmed, the number of passengers boarding and arriving at Mulgeum station is predicted to be 1,674 passengers/day by 2025. In addition, the numbers of train passengers that are converted from Ulsan and Gupo stations due to the stop at Mulgeum station are predicted to be 594 passengers/day boarding and 562 passengers/day arriving by 2025. In the future, if Yangsan citizens use the KTX Mulgeum station, the access time to Mulgeum station can be shortened to 22 minutes from 65 minutes, and it is predicted that the inconvenience of transferring between railroads will be resolved, with the waiting time for transfers reduced by up to a maximum of 40 minutes. Therefore, the economic effect of creating a KTX stop at Mulgeum station was analyzed to be B/C=1.823 when general railroad operating costs are not taken into account and B/C=2.127 when general railroad operating costs are considered. In conclusion, when using KTX trains to visit the Seoul Metropolitan Area, it takes 2 hours and 43 minutes to use Mulgeum station without using Ulsan station or Gupo station, which is considered to be very effective for reducing travel times and improving the economic feasibility of this development; it is also expected that Yangsan city will be able to improve accessibility and mobility to the Seoul Metropolitan Area by breaking free from the disgrace of being a remote location given its link to KTX in the future.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.182-185
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• 2011

본 논문에서는 국내 고속철도 차량 즉, 경부고속철도를 운행하는 KTX, KTX산천 그리고 현재 개발중인 HEMU400x을 대상으로 운행속도 및 운행패턴에 따른 열차 소비전력을 분석하였다. 이를 위해, 선로조건을 고려한 차량의 운전속도 조건과 운행시간,소비전력 등을 예측하기 위한 TPS(Train Performance Simulation)프로그램을 이용하였다. 열차운행 시뮬레이션을 수행하기 위해선 차량, 선로, 속도의 기본 데이터를 필요로 한다. 차량에 대한 데이터는 차량의 최고속도, 제동성능, 견인력 등의 기본 성능과 열차편성에 따른 중량, 길이, 동력차량형식, 열차주행저항등에 대한 제원을 요한다. 선로데이터는 운행시간 예측을 대상으로 하는 선로에 대한 거리별 구배 및 선형, 정거장 위치 및 정차시간에 대한 데이터이다. 속도조건은 구배 및 곡선에 대한 선로제한속도로, 선로데이터와 연계하여 각 선로위치별 차량의 제한속도로 이용된다. 본 논문에서는 경부고속철도 구간에서 운행하는 고속차량 3가지를 대상으로 증속에 따른 전력소모량을 비교하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.655-662
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• 2016

Accurate stopping control is important for trains, especially now that many train stations are equipped with platform screen doors. Various algorithms have been proposed for accurate stopping control. However, most metro trains in South Korea use classic control algorithms such as PID control because other algorithms are too complex to realize. PID control has merits of simple structure and operation. However, PID control sometimes fails, and much time is needed to find the proper coefficients due to the long control period and the brake delay. We propose a control algorithm that uses a Kalman filter. The Kalman filter estimates the states at the time when braking starts. Then, a suitable control input is derived for proper control. System modeling and a computer simulation were performed with consideration of the brake properties and the period of the control system. The superiority of the proposed control algorithm is shown by analyzing stop errors.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.72-79
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• 2021

This basic study introduces the concept of S-BRT and develops dwell time estimation models that consider road geometry and S-BRT characteristics for a signal operation strategy to meet the S-BRT's operational goal of high speed and punctuality. Field surveys of low-floor buses similar in shape to S-BRTs and data collection of passengers, station elements, vehicle elements, and other factors that can affect stop times were used in a regression analysis to establish statistically significant dwell time estimation models. These dwell time estimation models are developed by categorizing according to the locations of the signal or sidewalk that have the most impact on the dwell time. In this way, the number of people boarding and alighting the bus at the crowded door and the number of people boarding and alighting the bus at the front door considering the internal congestion was analyzed to affect the dwell time. The estimation dwell time models in this study can be used in the establishment of strategies that provide priority signals to S-BRTs.

• Fire Science and Engineering
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• v.22 no.1
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• pp.61-67
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• 2008

This study is focused on the numerical predictions of heat and smoke exhaust characteristics in an underground subway station stopping a fire train. Various ventilation operating modes with the fan equipped the platform and tunnels are considered. Distributions of temperature, carbon monoxide and visibility at a height of 1.7 m(breath height) above the platform are analysed for different ventilation fan operation mode. The numerical results show that smoke and heat is rapidly removed through tunnel by operating the tunnels fans. We suggested that during evacuation of passengers is not completed, the ventilation system in the platform is activated. After completion of passenger evacuation tunnel fans are activated but the fans in the platform are stopped.