• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.2
• /
• pp.1-12
• /
• 2016

This paper is to analyze characteristics of transfer trips and to identify impacts of land use on them. Using the smart transport card data of Seoul on a weekday in April 2013, we explored general characteristics of the transfer trips such as spatial and temporal distributions, transfer types, and geographical patterns of transfer trips. Then, the multiple regression model for the transfer trips was developed, considering land use as well as socio-economic variables as explanatory ones. For the characteristics of the transfer trips, their ratio to the total trips accounts for 26.7%. Nearly 87% of the trips are one-time transferred, and 64.7% are bus-subway transfer trips. In addition, the transfer trips are more likely to appear nearby subway stations and business facilities. The regression model indicates that land use variables such as the floor areas of business facilities and department stores and mixed land use index significantly positively affect the transfer trips. Our results can be used as basic data for choosing feasible locations of multi-modal transfer centers in urban areas.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.563-570
• /
• 2011

This study analyze the transfer patterns of passengers in Seoul based on transit smart card data that was observed in 2010. The smart card records maximum four times of transfer and reports that approximately 90% of trips were less than one transfer and the remains were more than 2 transfers. We focus on trips with more than 3 transfers to figure out the relationship between transit service and regional connectivities. The results show that the average travel time, distance, fare are 45 minutes, 18.3km, and 1,119(KW) respectively. We develope a map for investigating transfer patterns at a regional level(dong and gu). By doing this, three types of transfers are observed as: 1) trips of which origin and destination is either same or near, 2) trips with short distance, and 3) long distance trip with low transit connectivities.

• Journal of Korean Society of Transportation
• /
• v.32 no.3
• /
• pp.179-186
• /
• 2014

This study attempted to identify the characteristics of transfer trips between subways and buses in Daegu city and to analyze various impact factors that influence the number of transfer trips using a multiple regression analysis. Based on the results, this study aims to propose some policy implications to improve the operation efficiency of a transit center. As a result, it is found that the number of transfer trips is inversely proportional to transfer time, while directly proportional to the number of connected bus routes, subway's spatial location, and bus route connection index. Specifically, it is found that the number of transfer trips are mostly affected by bus route connection index.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.39 no.5
• /
• pp.613-621
• /
• 2019

In general, transfer in subway stations is defined as transfer between lines and station transfer. In transfer between lines, passengers change from one subway line to another by utilizing horizontal pedestrian facilities such as transfer passages and pedestrian way. Station transfer appears in the situation that subway lines of enter and exit gate terminals differs from those of boarding and alighting trains and passenger trips utilize both vertical pedestrian facilities such as stair and escalator and horizontal facilities. The hypothesis on these two transfers presupposes that all subway lines are operated by either local train or express in subway network. This means that in a transfer case both local and express trains are operated in the same subway line, as a case of Seoul Metro Line 9, has not been studied. This research proposes a methodology of finding the same line transfer in the Seoul metropolitan subway network built based on the smart card network data by suggesting expanded network concept and a model that passengers choose a theirs minimum time routes.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.04a
• /
• pp.234-241
• /
• 1996

Trip-based material handling systems such as AGV systems, lift trucks, etc. are often designed with a given flow matrix (or FROM-TO chart) which is usually treated as the number of loaded trips that the devices must perform per unit time between the stations. In reality, the number of trips that would result from parts flow in a facility is dictated by the transfer batch size, i.e., the number of parts that are transferred from one station to the next in one trip. In this paper, we present analytical and simulation results aimed at determining optimal or near-optimal transfer batch sizes in manufacturing systems.

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

• Journal of Korean Society of Transportation
• /
• v.24 no.3 s.89
• /
• pp.197-205
• /
• 2006

The study suggested a demand forecasting method which explicitly reflects transfer between various transport modes especially related light rail transit project with multi-modal transit system. The suggested method classifies several groups depending on characteristic of trips and applies different demand model for each group to explain travel pattern more realistically More specifically. the trips was classified by trips within the LRT route, trips between inside and outside of the LRT route. and through trips via the LRT route. The study also suggested a evaluation measurement of time saving due to the LRT construction, which are consistent along with the do-case and the do-nothing-case even though some mode shift could be happen after introducing the LRT.

• Journal of Korean Society of Transportation
• /
• v.34 no.5
• /
• pp.437-448
• /
• 2016

Some previous researches suggested a transit trip destination inference method by constructing trip chains with incomplete(missing destination) smart card dataset obtained on the entry fare control systems. To explore the feasibility of the transit trip destination inference method, the transit trip chains are constructed from the pre-paid smart card tagging data collected in Busan on October 2014 weekdays by tracing the card IDs, tagging times(boarding, alighting, transfer), and the trip linking distances between two consecutive transit trips in a daily sequences. Assuming that most trips in the transit trip chains are linked successively, the individual transit trip destination zones are inferred as the consecutive linking trip's origin zones. Applying the model to the complete trips with observed OD reveals that about 82% of the inferred trip destinations are the same as those of the observed trip destinations and the inference error defined as the difference in distance between the inferred and observed alighting stops is minimized when the trip linking distance is less than or equal to 0.5km. When applying the model to the incomplete trips with missing destinations, the overall destination missing rate decreases from 71.40% to 21.74% and approximately 77% of the destination missing trips are the single transit trips for which the destinations can not be inferable. In addition, the model remarkably reduces the destination missing rate of the multiple incomplete transit trips from 69.56% to 6.27%. Spearman's rank correlation and Chi-squared goodness-of-fit tests showed that the ranks for transit trips of each zone are not significantly affected by the inferred trips, but the transit trip distributions only using small complete trips are significantly different from those using complete and inferred trips. Therefore, it is concluded that the model should be applicable to derive a realistic transit trip patterns in cities with the incomplete smart card data.

• Journal of Arbitration Studies
• /
• v.18 no.3
• /
• pp.71-89
• /
• 2008

International technology transfer(ITT) or technology trade is a very comprehensive term covering various mechanisms and channels for shifting technologies across borders. Thus, it refers to numerous complex processes, ranging from innovation and international marketing of technology to its absorption and imitation. It includes technology, trade, and investment. Markets for exchanging technologies are inherently subject to failure due to appropriability problems, spillovers, asymmetric information, and market power. Thus, there is strong justification for public intervention. Technology developers are interested in reducing the costs and uncertainty of making transfers, along with protecting their rights to profit from such transfers. On the other hand, technology importers are interested in acquiring knowledge at minimal costs, asking for restricting sharply the exclusive rights of foreign firms to exploit technology. The purpose of this paper is to review the characteristics, risks, legal issues and contractual check points of ITT, focusing on the avoidance of commercial disputes during the very complex processes of ITT.

• Journal of Korean Society of Transportation
• /
• v.25 no.2 s.95
• /
• pp.121-132
• /
• 2007

This paper addressed the issue of a generalized cost model for transit assignment. The model composed of walk time, waiting time (including transfer waiting time), line-haul time, transfer walk time, and fare. The weights of each component were supposed to be calculated using the stated preference (SP) data, which were collected prudently in order to reflect reality. The marginal rate of substitution and wage rate were applied to calculate the weights. The results showed that the weight of walking time per in-vehicle travel time (IVTT) was 1.507, the weight of waiting time (per IVTT) was 1.749, that of transfer time (per IVTT) was 1.474, and that of fare (per IVTT) was 1.476 for trips between inner-city areas in Seoul. Weights for each component were identified as 1.871, 1.967, 1.015, and 0.857, respectively, for trips between Seoul and Gyeonggi. Statistical significance existed between two cases and each variable was also statistically significant. Transit assignment using the relative weights estimated in this study was implemented to analyze the travel index in a macroscopic and quantitative basis. The results showed that average total travel times were 30.23 minutes and 63.29 minutes and average generalized costs were 2,510 won and 3,880 won for trips between inner-city areas in Seoul and between Seoul and Gyeonggi, respectively.