• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.195-208
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• 2009

A network design problem (NDP) formulated as a mathematical program is generally used to find an optimum value to minimize or to maximize some objectives such as total travel time, social benefit, or others. NDP has, however, some limits of describing components of travel patterns like activities and trip generation due to its modeling simplicity, and also it has difficulty in including attributes of regional planning. In order to cope with such limits, this paper extends NDP to the urban planning field and proposes a mathematical program which can describe the interactions between urban social activities and transportation planning. Based on this model the authors try to optimize both urban activities and the transportation system. The model developed in this paper is tested to assess its application with a real-size regional transportation network.

• 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 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.

• 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.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.734-743
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• 2007

The KTX station is one of special generators that produce a lot of trips caused by special land use such as university, airport, and super shopping mall. Special generators need special attention in developing travel demand models since the standard trip generation and distribution model in the conventional four-step approach do not provide reliable estimates of their travel patterns. New modeling approach, activity-based model, considering travel behavior of person, seem to be more appropriate for those special generators. Thus, this study introduces a spatial-temporal activity-based approach and how activity-based approach can be applied to estimation of travel demand at KTX stations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.41-42
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• 2019

해양공간의 효율적인 활용과 해상사고 예방을 위하여 해상교통 현황 파악이 필요하다. 이를 위해서는 해상에서 운항하는 선박에 대한 면밀한 모니터링이 선행 되어야한다. 때문에 본 연구에서는 선박자동식별장치(Automatic Identification System, AIS)와 선박패스(V-Pass)를 활용하는 기존 모니터링 방법에서 나아가, 위성 자료를 활용한 연안 선박감시 방법을 해상교통관제(Vessel Traffic Service, VTS) 센터에서 활용하기 위한 방안을 제안한다. 위성 자료는 광범위한 영역에 대하여 다양한 정보를 획득할 수 있는 장점을 지니므로, 부산항 연안에서 수집한 AIS 데이터와 함께 딥 러닝 기반 선박 탐지 및 분류 모델에 활용함으로써, 보다 개선된 모니터링을 기대할 수 있다. 이를 활용하여 미식별 선박들의 출현 위치를 분석하고 나아가 선박의 종류를 예측함으로써, 상세한 해상교통 현황 파악 및 예측을 기대할 수 있다. 향후에는 선박의 종류 뿐 아니라 각 선박의 해상활동을 분석함으로써, 보다 체계적이고 실용적인 해양공간활용 계획수립에 도움이 될 수 있도록 개선할 계획이다.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.89-97
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• 2021

The objective of this study is to propose an operation management strategy for the connectivity which are the designated and managed in sector of the transportation and logistics on the national critical infrastructures. The industrial structure is becoming advanced. The national critical infrastructure managed by the shows forms of the cooperative connection and collaborative R&D. Also, in-depth and specific analysis for the disaster safety budget are implemented to consideration for the R&D life cycle. The government responsibility are expanded comprehensively. Needs are exchanging life styles by the economic and safety demands. At this trends, this study encourage facility maintenance and scientific management to the public service. Throughout the result of this study, national critical infrastructure are implementing for protection plan of the sustainable maintenance and management. And, we have to prepare and implement for the consideration of the characteristics through comprehensive guidelines. This study contributes to the disaster and safety management by proposed an operation strategy of the cooperative connection in the sector of transportation and logistic sector on the national critical infrastructure.

• Journal of The Korean Society For Urban Railway
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• v.6 no.4
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• pp.373-381
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• 2018

The floating population that is index to figure out dynamic activities in urban area will be important in urban railway planning, but it is not useful because it is collected by posterior method. This study aims to investigate factors influencing floating population. The floating population data that was collected in Seoul for a month in December 2013 is used as dependent variable, and the negative binomial regression analysis is used in modelling. The number of households, number of employees, number of subway stations, and number of bus lines variables are statistically significant in predicting floating population.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.89-108
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• 2006

Korea has been entering the ageing society as the population of age over 65 shared over 7% since the year 2000. The ageing society needs to have transportation facility considering elderly people's travel behavior. This study aims to understand the elderly people's travel behavior using recent data in Korea. The activity schedule approach begins with travel outcomes are part of an activitv scheduling decision. For tho?e approach. used discrete choice models (especially. Nested Logit Model) to address the basic modeling problem capturing decision interaction among the many choice dimensions of the immense activity schedule choice set The day activity schedule is viewed as a sot of tours and at-home activity episodes tied togather with overarching day activity pattern using the Seoul Metropolitan Area Transportation Survey data, which was conducted in June, 2002. Decisions about a specific tour in the schedule are conditioned by the choice of day activity pattern. The day activity scheduling model estimated in this study consists of tours interrelated in a day activity pattern. The day activity pattern model represents the basic decision of activity participation and priorities and places each activity in a configuration of tours and at-home episodes. Each pattern alternative is defined by the primary activity of the day, whether the primary activity occurs at home or away, and the type of tour for the primary activity. In travel mode choice of the elderly and non-workers, especially, travel cost was found to be important in understanding interpersonal variations in mode choice behavior though, travel time was found to be less important factor in choosing travel mode. In addition, although, generally, the elderly was likely to choose transit mode, private mode was preferred for the elderly over 75 years old owing to weakened physical health for such things as going up and down of stairs. Therefore. as entering the ageing society, transit mode should be invested heavily in transportation facility Planning tor improving elderly transportation service. Although the model has not yet been validated in before-and-after prediction studies. this study gives strong evidence of its behavioral soundness, current practicality. and potential for improving reliability of transportation Projects superior to those of the best existing systems in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.111-120
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• 2010

The policy which encourages people to use cars on the road has been based on the growth of economy in Korea. It has also caused the concentration and overcrowding in Seoul. That's because the increasing number of people possessing cars interconnects with the urban development. The transportation is a derived demand; so many scholars have recognized the importance of understanding the relationship between urban land use and transport. Considering such importance, this study theoretically compared the developed urban land use-transportation models each other and outlined the particular models briefly. Models were categorized by 2 types; optimizing model and predictive mode. Predictive model is also defined by static model, entropy based model, spatial-economic model, and activity model. After studying models, we investigated other major cities in America. This process is the pre-step for transport policy assessment. Through careful literature review, we can finally develop the integrated land-use transportation model in Seoul metropolitan area. In addition, we will be able to deal the changes of traffic demand pattern under U-Society. Consequently, the results of this study can be applied to ITS projects in the future.