• Journal of the Korean Society for Railway
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• v.18 no.5
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• pp.481-488
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• 2015

The recent trend in transportation planning information is to reduce traffic survey costs and enhance accuracy by using and converging various sources of external data. In Korea, mobile phone data can help generate useful transportation planning information, thanks to the universal use of mobile phones, which are present in a number greater than that of the population. This paper addresses measures to derive trip generation information from mobile phone data and verifies the value of the system for practical use by correlation analysis with KTDB trip generation data. The results show that trip generation information produced by mobile phone data correlates with existing (KTDB) trip generation data.

• Journal of the Korean Society for Railway
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• v.20 no.5
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• pp.588-594
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• 2017

Permanent magnet assisted synchronous reluctance motors (PMa-SynRM) show higher efficiency and power density compared to conventional induction motors for high speed railroad traction systems. Furthermore, 5-phase PMa-SynRMs have lower torque ripple and higher power density than 3-phase systems. Therefore, the 5-phase PMa-SynRM is suitable for high-speed railway traction systems. In this study, 3kw 3-phase and 5-phase PMa-SynRM models were optimized using lumped parameter model and genetic algorithm, and their characteristics were compared. The optimized models are fine-tuned using finite element analysis. The final models of the 3-phase and 5-phase PMa-SynRMs are fabricated and tested to verify the analysis results.

• Korean Journal of Construction Engineering and Management
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• v.22 no.6
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• pp.131-137
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• 2021

Since many resources are put into the work of changing the railway operation within limited time, it is important to have a specific work plan and safety management. For this reason, the work schedule is shared in advance, and parallel work is being carried out simultaneously by rail system, such as tracks, trolly wires, and signals. However, due to the nature of the transfer work, the work is carried out at night when the railway operation is finished, and many resources are put into the limited area of the operating line, so the risk of safety accidents and failure to change the operating line is recognized as high. Nevertheless, there is still not enough research done in korea regarding the operation line change construction. Therefore, this study is conducted a survey on the track exchange work of railroad for working people, and analyzed the results of the survey. Finally, a standard work process was suggested to reduce the risk of track exchange work.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.25-38
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• 2023

Seoul Metropolitan Urban Railroad has an undecided route that does not estimate the passenger transportation route. For this reason, the fare of the urban railroad is calculated by the assumption that passengers pass through the minimum distance. Therefore, if a transfer station on the urban railroad is added, the trip shortest distance could be decreased and the fare also reduced. In this study, this phenomenon defines the fare paradox(Shin, 2022) and estimates the impact of the fare paradox by opening the GTX-A. For this purpose, a scenario before and after the opening of the GTX-A has been established, and an additional fare has been estimated by proportional planning of the Seoul Metropolitan Integrated Distance Based Fare Policy. Fare Paradox was analyzed to about 0.024 % of daily income. It is expected to be used as a plan to determine a rate policy, such as the establishment of a GTX-A, B, C, D, and a light rail line.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.21-36
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• 2023

Activity-based modeling systems have increasingly been developed to address the limitations of widely used traditional four-step transportation demand forecasting models. Accordingly, this paper introduces the Activity-BAsed Traveler Analyzer (ABATA) system. This system consists of multiple components, including an hourly total population estimator, activity profile constructor, hourly activity population estimator, spatial activity population estimator, and origin/destination estimator. To demonstrate the proposed system, the emission impact of land use changes in the 5-1 block Sejong smart city is evaluated as a case study. The results indicate that the land use with the scenario of work facility dispersed plan produced more emissions than the scenario of work facility centralized plan due to the longer travel distance. The proposed ABATA system is expected to provide a valuable tool for simulating the impacts of future changes in population, activity schedules, and land use on activity populations and travel demands.

• Journal of the Korean Society for Railway
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• v.17 no.1
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• pp.59-69
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• 2014

Recently, the building of an intermodal transportation system has become the most important policy in the establishment of a national-wide sustainable transport system. In the case of rail and public transport, an intermodal connecting improvement policy is essential due to the lack of trip completeness. In particular, high-speed rail has brought dramatic changes to the transportation system in Korea and the idea of high-speed rail stations as major transportation nodes to be linked to various travel modes needs to be analyzed in terms of an intermodal network. Thus, this study proposes a new connectivity analysis method to objectively and quantitatively evaluate intermodal connecting performance for high-speed rail in terms of an intermodal network around high-speed rail stations. Seoul, Busan, Ulsan, and Sin-gyeongju stations were designated for a range of spatial analyses; detailed connecting performance indexes of travel modes connecting high-speed rail stations, and the influence sphere of these stations are analyzed, except for internal transfer facilities. Finally, this study proposes a connectivity analysis method that applies the structural equation model and develops a connectivity index.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.585-601
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• 2004

The purpose of this paper is to examine the change of Korean land transportation system and pattern during 1905-1911 concentrated on road construction so-caued ‘Sinjak-ro’. As conclusions, modem road or ‘Sinjak-ro’ started from modem port to inner hinterland where economic resource or regional center located. A trunk railroad running through Korea Peninsula from Busan to Sinuiju(border between China) is opened its complete operation in 1906 by Japanese investment, when no ‘Sinjak-ro’ road construction begun. Thus from the beginning, railroad station also became important starting point of ‘Sinjak-ro’ as seaports. Before the Japanese annexation of Korea, the ‘Sinjak-ro’ road was constructed mainly between seaport or station, where Japanese commercial settlement located, and hinterlands to help their economic invasion. This study could not deal with other modem transportation systems such as railroads and waterways. It is necessary to examine whole changes of modern transportation systems in this age so that we would comprehend modernization feature of Korea from the viewpoint of transportation history.

• Asian Journal of Atmospheric Environment
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• v.5 no.1
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• pp.41-46
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• 2011

The port of Busan is the fifth busiest container port in the world in terms of total mass of 20-foot equivalent units transported. Yet no attempts have been made to estimate the greenhouse gas (GHG) emissions from the port of Busan by accounting for all port-related activities of the various transportation modes. With these challenges in mind, this study estimates the first activity-based GHG emissions inventory in the port of Busan, which consists of four transportation modes: marine vessels, cargo-handling equipment, heavy-duty trucks, and railroad locomotives. The estimation results based on the most recent and complete port-related activity data are as follows. First, the average annual transportation GHG emission in the port of Busan during the analysis period from 2000 to 2007 was 802 Gg $CO_2$-eq, with a lower value of 773 Gg $CO_2$-eq and an upper value of 813 Gg $CO_2$-eq. Second, the increase in the transportation-related GHG emissions in the port of Busan during the analysis period can be systematically explained by the amount of cargo handled ($R^2$=0.98). Third, about 64% of total GHG emissions in the port of Busan were from marine vessels because more than 40% of all maritime containerized trade flows in the port were transshipment traffic. Fourth, approximately 22% of the total GHG emissions in the port of Busan were from on-road or railroad vehicles, which transport cargo to and from the port of Busan. Finally, the remaining 14% of total GHG emissions were from the cargo handling equipment, such as cranes, yard tractors, and reach stackers.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.23-31
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• 2020

This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

• Journal of the Korean Society for Railway
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• v.19 no.3
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• pp.314-323
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• 2016

Overhead line voltage of DC railway traction substations has rising or falling characteristics depending on the acceleration and regenerative braking of the subway train loads. The suppression of this irregular fluctuation of the line voltage gives rise to improved energy efficiency of both the railway substation and the trains. This paper presents parameter estimation schemes using the RC circuit model for an overhead line voltage at a 1500V DC electric railway traction substation. A linear artificial neural network with a back-propagation learning algorithm was trained using the measurement data for an overhead line voltage and four feeder currents. The least square estimation method was configured to implement batch processing of these measurement data. These estimation results have been presented and performance analysis has been achieved through raw data simulation.