• Journal of Korea Port Economic Association
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• v.32 no.4
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• pp.165-182
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• 2016

This study examines the competitiveness and cooperativeness among the container ports in East Asia by analyzing their monthly dynamics in eight years (2008-2015). Time series data on container throughput divided into origin and destination (O/D), such as the top six Chinese ports and the transshipment (T/S) ports such as Hong Kong, Busan, and Singapore, are computed with two methods based on the Vector Error Correction Model (VECM). The first Granger causality test results show that Busan T/S has significant bilateral relations with three Chinese O/D ports; and significant unidirectional relations with three other O/D ports. Shenzhen port has significant bilateral relations with Singapore, and has a significant unidirectional relation with Hong Kong port. Co-integrating test results showed that Busan holds negative co-integration with all Chinese O/D ports. Impulse response function (IRF) results show an opposite direction between paired ports. The ratios of the impulse from T/S ports are significantly high to one another in the short-run, but its power declines as time passes. The ratio of the impulse from the Chinese ports to T/S ports is less significant in the short-run period, however, it becomes more significant as time passes. The significance of most shocks was high in the second period, but was diluted after the sixth period.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.1
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• pp.44-63
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• 2007

The purpose of this study is to propose mining processes in the large trip-transaction database of the Metropolitan Seoul area and to analyze the spatial characteristics of travel behavior. For the purpose. this study introduces a mining algorithm developed for exploring trip patterns from the large trip-transaction database produced every day by transit users in the Metropolitan Seoul area. The algorithm computes trip chains of transit users by using the bus routes and a graph of the subway stops in the Seoul subway network. We explore the transfer frequency of the transit users in their trip chains in a day transaction database of three different years. We find the number of transit users who transfer to other bus or subway is increasing yearly. From the trip chains of the large trip-transaction database, trip patterns are mined to analyze how transit users travel in the public transportation system. The mining algorithm is a kind of level-wise approaches to find frequent trip patterns. The resulting frequent patterns are illustrated to show top-ranked subway stations and bus stops in their supports. From the outputs, we explore the travel patterns of three different time zones in a day. We obtain sufficient differences in the spatial structures in the travel patterns of origin and destination depending on time zones. In order to examine the changes in the travel patterns along time, we apply the algorithm to one day data per year since 2004. The results are visualized by utilizing GIS, and then the spatial characteristics of travel patterns are analyzed. The spatial distribution of trip origins and destinations shows the sharp distinction among time zones.

• Journal of Korean Society of Transportation
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• v.31 no.3
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• pp.74-85
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• 2013

We analyze the efficiency of congestion pricings and transit subsidies in the spatial micro-economic model based on a general equilibrium environment. In this setting, we decompose the total welfare change into component factors and identify the reason of the change in the efficiency caused by policy instruments; these component factors are divided into indirect factors and direct factors including of origin-destination and mode choices. We set up the model as adding mode choice to the standard format in the fashion of Anas and Kim (1996) and extend the methodology proposed by Yu and Rhee (2011) and Rhee (2012) for deriving theoretical and analytical solution. Most of welfare gain comes from the modal shift from car to bus. The relative efficiency of subsidies in relation to the first-best pricing is lower than it of congestion pricings although the change in bus share by subsidies is similar to it by congestion pricing. Subsidies give rise to more modal shift from a car to a bus for long-distance commuting than it caused by congestion pricings. As the increase of bus share for long-distance commuting leads to the increase of cross-commuters passing through CBD, the welfare gain by subsidies is lower than it by congestion pricings.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.36-46
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• 2016

Separate transportation card readers that record the amount of transfer volume occurring during movement in-between lines within the metropolitan railway transfer stations do not exist. This research proposes a model to estimate passenger transit movements in transfer stations that adequately reproduces characteristics arising during a transfer trip. The model used in this study assumes that passengers adopt transfer behaviors that minimize their generalized costs during transfer trips. Further, two measures are sought in order to reflect attributes of the metropolitan railway. The first is that similar paths connect origin and destination stations. For this, the M-Similar Paths method is applied to the model to identify the similar paths that arise. The second is that passengers perceive increasing number of transfers as additional transfer costs, which is reflected by means of the Stepwise Transfer Coefficient. Two case studies of metropolitan railway are used to propose measures for analysis of transfer trips. Twenty directional transit phenomena are reproduced for Sindorim railway station. Aggregate directional transit(A), aggregate inter-line transit(B), and B/A are calculated on a percentage basis for 33 metropolitan railway transfer stations, and using this, the functional role of transfers is explored.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.1
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• pp.85-91
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• 2021

In contrast to standard train tracks, tramlines are often set along public roads, with trams running among pedestrians and other vehicles. In some cities and towns, trams and buses share the same routes and stations. Under the current investment appraisal system, trams are classified into light rail when predicting traffic demand and calculating benefits, but in the case of non-capital areas, it is notable that the origin-destination and transit lines of buses are not provided in the Korea Transport Database distribution data. Due to this problem, it is difficult to reflect proper mode changing behaviors between route buses and trams. This study examines the impact on tramlines of bus routes that are not currently considered in non-capital areas. Following an analysis of the effect of tram projects according to whether bus routes are considered or not, an improvement in methodology is proposed. Through this study, it is expected that the investment appraisal system for the planning of new tramlines will be improved in the future.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.155-168
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• 2018

In this study, we studied the directional pattern of entering the intersection from the intersection upstream link prior to predicting short future (such as 5 or 10 minutes) intersection direction traffic volume on the interrupted flow, and examined the possibility of traffic volume prediction using traffic assignment model. The analysis method of this study is to investigate the similarity of patterns by performing cluster analysis with the ratio of traffic volume by intersection direction divided by 2 hours using taxi DTG (Digital Tachograph) data (1 week). Also, for linking with the result of the traffic assignment model, this study compares the impact area of 5 minutes or 10 minutes from the center of the intersection with the analysis result of taxi DTG data. To do this, we have developed an algorithm to set the impact area of intersection, using the taxi DTG data and traffic assignment model. As a result of the analysis, the intersection entry pattern of the taxi is grouped into 12, and the Cubic Clustering Criterion indicating the confidence level of clustering is 6.92. As a result of correlation analysis with the impact area of the traffic assignment model, the correlation coefficient for the impact area of 5 minutes was analyzed as 0.86, and significant results were obtained. However, it was analyzed that the correlation coefficient is slightly lowered to 0.69 in the impact area of 10 minutes from the center of the intersection, but this was due to insufficient accuracy of O/D (Origin/Destination) travel and network data. In future, if accuracy of traffic network and accuracy of O/D traffic by time are improved, it is expected that it will be able to utilize traffic volume data calculated from traffic assignment model when controlling traffic signals at intersections.