• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.63-74
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• 2010

Recently, there has been increasing demand from academic society in Korea for the improvement of current traffic congestion cost estimation methods. The purpose of this study is to suggest a better way to estimate congestion cost followed by in-depth review regarding traffic congestion. The key improvements proposed in this study include: 1) adding social externality to congestion cost, 2) integrating the green house and environmental pollution impacts with congestion costs, 3) taking non-recurrent traffic congestion costs into account for the assessment, 4) revising the criteria to determining the level of traffic congestion speed, and 5) deciding how to limit congestion measurement period. It is found meaningful that the improvements, notwithstanding difficulties in their real case application, provide invaluable insights in our efforts to change the meaning of congestion cost in an era of sustainable growth.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.44-53
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• 2016

The era of Big Data has come and the importance of Big Data has been rapidly growing. The part of transportation, the Four-Step Travel Demand Model(FSTDM), a traditional Trip-Based Model(TBM) reaches its limit. In recent years, a traffic demand forecasting method using the Activity-Based Model(ABM) emerged as a new paradigm. Given that transportation means the spatial movement of people and goods in a certain period of time, transportation could be very closely associated with spatial data. So, I mined Spatial Big Data from SNS. After that, I analyzed the character of these data from SNS and test the reliability of the data through compared with the attributes of TBM. Finally, I built a database from SNS for the operation of ABM and manipulate an ABM simulator, then I consider the result. Through this research, I was successfully able to create a spatial database from SNS and I found possibilities to overcome technical limitations on using Spatial Big Data in the transportation planning process. Moreover, it was an opportunity to seek ways of further research development.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.33-43
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• 2006

This research is to the selection of optimal probability distribution as well as the estimation for design hourly factor in consideration of traffic characteristic, such as road function, lane number and AADT. To accomplish the objectives, we are applied to various probability distribution using traffic data that observed at permanent traffic count points in 2005. The parameters or the selected 14 probability distribution were estimated based on the method of maximum likelihood and the validity condition of the estimated parameter The goodness-of-fit test, such as chi-square test. was performed as well as the estimation of design hourly factor. As a result, An appropriate distributions of each case were selected : Pearson V for two lane of rural roads, LogLogistic for the four lane of rural roads, LogLogistic for the urban roads, Extreme value for recreation roads. And optimal K factor are as following : $0.1{\sim}0.2 $ for two lane of rural roads, $0.09{\sim}0.14$ for the four lane of rural roads. $0.07{\sim}0.13$ for the urban roads, $0.1{\sim}0.2$ for recreation roads.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.101-111
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• 2017

This study propose a method to predict the bus arrival time by considering the signal delay time which is an element which can not be considered in the current bus arrival prediction information generation algorithm. In order to consider the signal delay time, travel time is divided into three components: service time, cruising travel time, and signal delay time. Signal delay time was estimated using intersection arrival time and TOD. The results show that most of the errors that occurred in predicting the arrival time are within about 30 seconds. Some of the estimates have large errors due to the nature of this methodology that uses the estimated value of the intersection arrival time rather than the observation value. It is also difficult to predict the arrival time of the express buses using this method. Future studies such as improving this through real-time location information will greatly improve the accuracy of the methodology.

• Journal of Korean Society of Transportation
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• v.28 no.6
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• pp.133-146
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• 2010

The objective of this study is to develop a supply chain-based freight distribution channel choice model considering shippers' logistics behaviors which will be used for freight demand estimation. For this purpose, this study utilized the distribution channel data of the petrochemical and automobile industries collected by KTDB center. The distribution channel choice models for these industries were developed by including transport mode, time, cost, and shipment size. It was found that the multinomial logit model with transport cost, time and shipment size is the best, and as shipment increases, bigger transport mode is preferred. Generally direct distribution channel with small truck was preferred over the one using distribution center and/or big truck.

• Journal of Korean Society of Transportation
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• v.33 no.5
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• pp.461-469
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• 2015

The next generation high-speed train, HEMU-430X, was developed and is now being tested. However, the existing mode choice models based on the guidelines for feasibility studies do not consider a high-speed train with a higher speed than KTX. This limitation might result in inaccurate demand forecasting. In this research, a stated preference survey was conducted in order to supplement the problem by considering the characteristics of HEMU-430X. Based on the survey results, this research developed two mode choice models, including a multinomial logit model and a nested logit model. For this purpose, the utility functions of travel time and travel costs were estimated using a Limdep 8.0 NLOGIT 3.0 package. After comparing the two models, it was concluded that the nested logit model is appropriate. The paper suggested a plan to implement the nested logit model and presented a policy implication.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.544-553
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• 2014

Activity-based models analyze individuals' various daily activities that are identified as a decision-making unit for transportation planning. In other words, it is the model that determines the types of activities according to the social, economic and situational characteristics of the groups with the same activity patterns and predicts individuals' activity time, distance, spatial movement and transportation mode. The activity-based model is a method of estimating more efficient and realistic demand in transportation forecasting because traffic is regarded as a complex decision-making process that an individual and other people participate in. In this paper, we grasp the factors affecting choice behavior of activity pattern and analyze choice behavior of activity pattern based on multi-dimensional characteristic of each person. First, we classify activity types of reviewing the trip chain and activity purpose. Next, we identified preferable activity types using complicated characteristics of main agent of activity. We concluded that choice behavior of activity pattern is dependent on complex characteristics of each agent, and further multi-dimensional characteristics of each person are affected over the whole decision process of activity schedule.

• Journal of Korea Port Economic Association
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• v.33 no.3
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• pp.17-34
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• 2017

This study aims to analyze the freight transport demand and benefit for the introduction of an automated freight transport system focusing on the Global Industry and Logistics City (GILC) in Busan. In pursuit of this aim, four alternatives were calculated - using the freight volume estimating methods and included, the number of businesses, the number of employees set up, future estimated cargo volume, and switched volume from other transport modes into the GILC. Economic benefits were analyzed against social benefits and costs accordingly. The result of the freight transport demand forecast found, the cargo volume of "Alternative 2-1" to be the most advantageous, applying the number of employee unit method and proportion of employees in Gangseo-gu, Busan. In addition to the conventional analysis of direct benefit items (reduction of transport time, traffic accidents and environmental costs), this study also considered additional benefit items (congestion costs savings, and road maintenance costs in terms of opportunity cost). It also considered advanced value for money research in guidance on rail appraisal of U.K, Federal Transport Infrastructure Plan 2003 of Germany, and RailDec of the United States. The study aims to further contribute to estimating minimum cargo transport demands and assess the economic feasibility of the introduction of new intermodal automated freight transport systems in the future.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.567-578
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• 2014

The study suggested a method to improve analysis accuracy such that the interactive effects of transportation changes between outside and inside of sub-areas were sequentially considered in the analysis by linking a macroscopic network analysis and a microscopic traffic simulation. A dynamic O/D estimation method was developed for practical implement of sub-area microscopic simulation analysis by using the results of macroscopic network analysis, the results of selected link analysis at the cordon line of the sub-area, departure time data of household travel survey, timely observed traffic volume data at the cordon. This estimated dynamic O/D for the sub-area made it possible to analyze traffic phenomena in details. Various detailed phenomena such as traffic queues, delay at intersection, and conflicts between vehicles, which is impossible to be grasped through a macroscopic analysis, can be analyzed with the dynamic microscopic traffic analysis. Through implementing an empirical study and validation, the study provided a reference result about accuracy of a microscopic traffic simulation of a sub-area to help its application for real transportation policy analysis.

• Journal of Korean Society of Transportation
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• v.27 no.3
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• pp.131-140
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• 2009

A diversity of railway network function enhancement projects such as the double tracking, electrification, and direct operation have been actively executed to improve the railway service. When the new rapid railway is provided, how many people will use it instead of other transports? How will the railway choice behavior be changed? Accordingly, in this paper, the applicability of diverted travel demand forecast method by Stated Preference(SP) and Transfer Price(TP) data was reviewed for Daegu metropolitan railway service. As the result of implementing the Revealed Preference(RP) and RP+SP model, the total travel time and travel cost parameters are of the right sign and are highly significant. In particular, when TP data is used as the complementary investigation of SP, the boundary value of diverted travel demand can be easily identified by railway fare and travel time service level. Therefore, it is considered that this will practically apply even in other regions as well as Daegu metropolitan railway.