• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1559-1569
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• 2013

this study is to deduct the difference between regional and urban commercial trips by analyzing the characteristics of the regional and urban truck movements. To achieve this, we investigated the relation between the number of truck trips and various truck generation attributes such as truck attributes, origin and destination attributes, and commodity type using ordered logit models, which are separately estimated for regional and urban truck movements using truck diary data of Korea Transport Database (KTDB). According to the estimation results, regional and urban truck movements have different characteristics in truck attributes, origin and destination attributes and commodity type. Especially, the number of regional trucks trips increased as origin and destination are manufactural area and as the total value of products of industrial area in origin and destination increase.

• Journal of the Korean Society for Railway
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• v.16 no.1
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• pp.59-64
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• 2013

This study analyzed passenger access and egress travel patterns related to a Korean regional railway station (Seoul station), then developed a binomial logit model. This model referred to bus and metro mode of access and egress during a national holiday (Chuseok 2009); obtained from transit smart card data. The results showed that 99% of passengers getting access to, or egress from, the regional railway station did so using less than two transfers, and that most passengers were more likely to choose a metro. However, the passengers that made access or egress trips near Seoul Station were more likely to take a bus. From the results of the mode choice model, it was found that the impact of travel time was greater than that of travel cost, in the choices made for both access and egress. Interestingly, the impact of travel time is much greater in choosing the mode of egress.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.47-57
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• 2012

The purpose of this study is to propose a supplement to current freight demand model by analyzing factors that influence the generation of empty truck movements in regional and urban realms. To achieve this, we examined the relation between the number of empty truck trips and various generators such as truck attributes, origin type and attributes, destination type and attributes, and commodity type. We structured the ordered logit model using 2011 Korea Transport Database (KTDB) data to analyze the generator characteristic of empty truck movements in regional and urban settings. According to the results, the characteristics of regional and urban empty truck movements differed depending on truck attributes, origin type and attributes, destination type and attributes, and commodity type.

• Journal of the Korean Society for Railway
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• v.12 no.4
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• pp.488-498
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• 2009

The characteristics of intercity rail network are different from those of public transit network in urban area. In this paper, we proposed a new transit assignment model which is generalized form of deterministic assignment model by introducing line selection probability on route section. This model consider various characteristics of intercity rail and simplify network expansion for appling search algorithms developed in road assignment model. We showed the model availability by comparing with existing models using virtual networks. The tests on a small scale network show that this model is superior to existing models for predicting intercity rail demand.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.7-16
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• 2008

There are unique aspects of truck vehicle movements compared with the personal travel in trip chaining. This paper reports an analysis on the truck vehicle trip chaining which intercity/metropolitan/intraregional trips are classified. Data collected from the travel dairy survey is used the truck trip-chaining analysis. The pattern of trip chaining classes is classified by the GIS mapping based on orgin-destination trip information. The physical index and efficiency index for each trip diary is used to the truck vehicle activity. Truck trips lengths and time differs from its truck type, service type and travel patterns. It is shown that the efficiency of the truck trip chaining depends on vehicle types and its delivery patterns. There are many other topics for research on trip chaining modeling such as the classification of trip chain, time use and mode choice by trip chaining.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.481-498
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• 2017

Travel time reduction benefit is the most important benefit item in the feasibility study of transportation infrastructure investment projects and calculated by using the value of travel time. The current feasibility study guideline (5th edition) calculate the value of non-business ravel time in a metropolitan area, using the ratio of the value of non-business travel time to business travel time calculated based on the nationwide inter-regional traffic survey data of 1999. The characteristics of metropolitan trips are different from those of nationwide regional trips. Metropolitan trips have frequent transfers between multiple public transits and long-time commuter trips. Therefore, this research aims to calculate the value of travel time reflecting traffic characteristics in a metropolitan area by improving the limitation of current calculation methods. To reflect these characteristics, this research extracts commuter trips from non-business trips and calculates the value of travel time for commuter trips. The results of the likelihood ratio test for the commuter trip model and the non-business trip model are found to be statistically significant. An integrated public transportation model was also estimated in this study to reflect the trip conditions of the Seoul metropolitan area integrated fare system. The results of comparing coefficients between bus and subway in the integrated public transit model indicated that there were no statistically significant differences between the two modes.

• Journal of Korean Society of Transportation
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• v.31 no.4
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• pp.47-57
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• 2013

This study aims at analyzing transportation equity between geographical areas of Gyonggi Province, by taking both the transportation infrastructure and travel behavior into account. Indicators of transportation infrastructure include the indices of road infrastructure, transit infrastructure and regional characteristics. Travel behavior concerns information from bus card data on a survey day. The hot-spot analysis conducted included spatial cluster analysis and global/local regression analyses. The analysis results identified geographical areas of four different classes of transportation equity, from the area with high level infrastructure surrounded by the areas with high level infrastructure (HH) to the area with low level surrounded by the areas with low level (LL). The area of HH type showed big numbers of passengers, trips and transfers, whereas the area of LL type shows big figures of internal trip frequency, travel time, travel distance, travel speed and transit fare. Global regression analysis showed that number of passengers, number of transfers, number of internal trips and mean travel speed are important to the level of transportation infrastructure. GWR with these four significant variables significantly improved the AICs and ANOVA results, which implies that the infrastructure is likely explained by travel characteristics differently between geographical areas in Gyonggi Province.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.379-395
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• 2006

The purpose of this study is to analyze the spatial characteristics of travel patterns and travel behaviors of transit users in the Metropolitan Seoul area. We apply the data mining techniques to explore the travel patterns of transit users from the T-money card database which has been produced over 10,000,000 transaction records per day. The database contains the information of locations and times of origin, transfer, and destination points for each transaction as well as the informations of transit modes taken via the transaction. We develop an data mining algorithm to explore traversal patterns from the enormous information. The algorithm determines the travel sequences of each passenger, and produce the volumes of support on each points (stops) of transportation networks in the Metropolitan Seoul area. In order to visualize the spatial patterns of travel demands for transit systems we apply GIS techniques, and attempt to investigate the spatial characteristics of travel patterns and travel demand. Subway stops located in the Gangnam area appear the highest peak for the travel origin and destination, while the CBD in the Gangbuk stands at the second position. Two or three sub-peaks appear at the densely populated residential areas developed as the high-rise apartment complex. Subway stations located along the Subway Line 2, especially from Guro to Samsung receive heavy travel demand (total support), while bus stops located at the CBD in the Gangbuk stands the highest travel demand by bus.

• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.109-119
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• 2007

Increasingly, the emphasis in regional Passenger rail Planning is finding ways to more efficiently use existing facilities, with particular attention being Paid to Policies designed to spread Peak-Period travel demand more evenly throughout the week with consideration of train classification. In this context the individual's choice of time to travel is of crucial significance. This paper investigates the use of multinomial logit analysis to model ridership by rail classification using data collected for travel from Seoul to Busan during the one week in October 2004. The Particular model form that was successfully calibrated was the multinomial logit (MNL) model : it describes the choice mechanism that will Permit rail systems and operations to be planned on a more reliable basis. The assumption of independently and identically distributed(IID) error terms in the MNL model leads to its infamous independence from irrelevant alternatives (IIA) property. Relaxation of the IID assumption has been undertaken along a number or isolated dimensions leading to the development of the MNL model. For business and related rail travel patterns, the most important variables of choice were time and frequency to the chosen destination. The calibrated model showed high agreement between observed and Predicted market shares. The model is expected to be of use to railroad authorities in Planning and determining business strategies in the Increasingly competitive environment or regional rail transport.

• Journal of Korean Society of Transportation
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• v.24 no.7 s.93
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• pp.15-25
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• 2006

This study was to investigate the impact of region-wide travel pattern on local fiscal capacity in the Seoul metropolitan area. The study adopted both factor analysis and regression modeling for it, while using fiscal-and travel-related variables as well as urban characteristics determining travel patterns. We used the former method to compress independent variables of travel and urban characteristics because of strong correlationship between them. Four factors identified by the analysis output were adopted in regression models with some dependent variables representing local fiscal capacity. Their results resulting from both analyses showed that local fiscal inequality within the metropolitan area is driven by region-wide travel Patterns such as total trips. inner trip ratio, and the ratio of trips from and to the Seoul city.