• Journal of Korean Society of Transportation
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• v.1 no.1
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• pp.82-103
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• 1983

본 연구는 1980년 Moses-Anas에 의해 제안된 $\ulcorner혼성로-짓모형\lrcorner$의 유효성을 서울 시의 출근통행실태 자료를 이용하여 검증하기 위한 것으로, $\ulcorner혼성로-짓모형\lrcorner$에 의한 추정 결과와 $\ulcorner전통적로-짓모형\lrcorner$에 의한 추정결과를 통계적 시점에서 상호 비교하였다. 이용된 자료는 1981년6월10일부터 6월16일까지 일주일간의 출근통행실태자료이며 조사표본수는 약 2000여 표본이었다. $\ulcorner혼성로-짓모형\lrcorner$에 의한 추정결과는 $\ulcorner전통적로-짓모형\lrcorner$ 에 의한 경 우보다 통계적으로 우월한 것으로 나타났으며, 특히 통행시간 및 통행비용에 대한 선택확률 의 탄력성은 $\ulcorner혼성모형\lrcorner$에 의해 추정된 결과가 더욱 합리적인 것으로 판명되었다.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.87-97
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• 2008

The traditional trip-based modeling approach has assumed that a trip is generated for a purpose. However, the approach has not considered trips as a set of connected trips nor has it considered trip chaining. The purpose of this study is to identify general characteristics of trip chaining, and to explore relationships between trip purposes and trip chains using multivariate regression models. The data for this study come from the 2006 Seoul household travel diary survey. It is found that simple trip chains are dominant phenomena, and socio-economic characteristics such as occupation, income, age, and gender are closely related to types of trip chains. People aged less than 20, females, or high-income people are more likely to have a higher number of home-based trip chains. In addition, commute and school trips for workers and students respectively tend to be strongly associated with simple trip chains, while shopping and leisure trips for housewives tend to be related to simple trip chains.

• Journal of Korean Society of Transportation
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• v.35 no.1
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• pp.1-10
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• 2017

The compact city usually provides good accessibility of residents with multiple transportation modes. However, in a compact city, annual average of travel distance per household by car is relatively short due to more congested traffic condition and larger travel cost than disperse city. As a result, total travel demand is decreasing when the region becomes more compact. Therefore compact development is regarded as one of the sustainable choices for future urban planning in many countries. This study aims at an empirical analysis of the relationship between urban compactness and travel demand based upon land-use and travel data for city of Seoul. In this study, 424 sub-districts with the mixed land-use patterns are assessed in a hexagonal diagram. The measurement is based on the relative deviation of each sector's characteristics including numbers of residence, manufacture, and trade & service. Multiple linear regression models are developed to analyze the effects of urban compactness on zonal trip generations. As a result, the trip generation rate in the residence-intensive and mixed-use areas is found to be relatively low. Furthermore, residents in high-compact areas tend to use public transport more often than residents in less compact areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.44-57
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• 2019

It is crucial to understand how people make decisions on mode choice and to accurately predict their behaviors in transportation planning. One of avenues for advancing modeling is, in particular, taking into account for taste heterogeneity in modeling that can incorporate different decision-making processes across group. In this study, we hypothesize that how people make decisions on mode choice would differ by destination in that land use characteristics are heterogeneous by zone even if zones are all in the same area. To this end, we apply Latent Class Modeling (LCM) to commute trips in Seoul by using 2010 household travel diary survey, investigate types of latent classes with the aid of characteristics of destination, and analyze how those classes differently response to factors. The LCM identifies two classes: in the first one, modal split of auto and public transit (bus and metro) is almost half-and-half and the trip destinations are characterized by relatively more residence facilities and less business/commercial facilities; in the second one, public transit has a notably high share and trip destinations are characterized by relatively more business/commercial facilities. In addition, it turns out that demographic and socio-economic variables affect mode choice differently by class.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.143-155
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• 2009

A dynamic traffic assignment (DTA) has recently been implemented in many practical projects. The core of dynamic model is the inclusion of time scale. If excluding the time dimension from a DTA model, the framework of a DTA model is similar to that of static model. Similar to static model, with given exogenous travel demand, a DTA model loads vehicles on the network and finds an optimal solution satisfying a pre-defined route choice rule. In most DTA models, the departure pattern of given travel demand is predefined and assumed as a fixed pattern, although the departure pattern of driver is changeable depending on a network traffic condition. Especially, for morning peak commute where most drivers have their preferred arrival time, the departure time, therefore, should be modeled as an endogenous variable. In this paper, the authors point out some shortcomings of current DTA model and propose an alternative approach which could overcome the shortcomings of current DTA model. The authors substitute a traditional definition for time-dependent OD table by a new definition in which the time-dependent OD table is defined as arrival time-based one. In addition, the authors develop a new DTA model which is capable of finding an equilibrium departure pattern without the use of schedule delay functions. Three types of objective function for a new DTA framework are proposed, and the solution algorithms for the three objective functions are also explained.

• Journal of Korean Society of Transportation
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• v.36 no.3
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• pp.203-215
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• 2018

This study suggests a method to construct large scale dynamic O/D reflecting the characteristic that the passengers' travel patterns change according to the land use patterns of the destination. There are limitations in the existing research about dynamic O/D estimation method, such as the difficulty of collecting data, which can be applied only to a small area, or limiting to a specific transportation network such as highway networks or public transportation networks. In this paper, we propose a method to estimate dynamic O/D without limitation of analysis area based on transportation resources that can be easily collected and used according to the big data era. Clustering analysis was used to calculate the departure time trip distribution ratio based on arrival time and departure time trip distribution function was estimated by each cluster. As a result of the comparison test with the survey data, the estimated distribution function was statistically significant.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.193-204
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• 2022

Smart card data is representative mobility data and can be used for policy development by analyzing public transportation usage behavior. This paper deals with the problem of classifying metro stations using metro usage patterns as one of these studies. Since the previous papers dealing with clustering of metro stations only considered traffic among usage behaviors, this paper proposes clustering considering traffic time as one of the complementary methods. Passengers at each station were classified into passengers arriving at work time, arriving at quitting time, leaving at work time, and leaving at quitting time, and then the estimated shape parameter was defined as the characteristic value of the station by modeling each transit time to Weibull distribution. And the characteristic vectors were clustered using the K-means clustering technique. As a result of the experiment, it was observed that station clustering considering pass time is not only similar to the clustering results of previous studies, but also enables more granular clustering.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.97-108
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• 2001

A dynamic transportation management should be applied specially in AM peak because AM peak is more critical than PM peak in traffic volume and demand. AM peak trip can be characterized by commuting and schooling. which have the high level of usage on public transportation, and constraint on arrival time. So transportation management applied in AM peak could deal with a mode choice and an arrival time constrain. Researchers were involved in the dynamic transportation assignment models for management of congested traffic network. But, there were no models which considered a mode choice and an arrival time constrain should be included in management of AM peak. So there are limits to use exist models to control and analyze AM peak traffic. In this study, it is proposed the combined dynamic transportation model, considering a mode choice and the start time selection with arrival time constrains, based on Ran and Boyce's model. The proposed model is verified the compatibility by applying to the newly designed time space expanded network. The result shows that proposed model consistent with dynamic user optimal travel pattern. From this we certificate the applicability of the proposed model to control and analyze AM peak traffic.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.709-716
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• 2006

The rapid changes of family structure such as singles, working couples and so on have effects on a travel behaviour. One of the characteristics from this is the increasing portion of trip-chain, in which plural activities were conducted in a "single outgoing" travel. Therefore travel must be considered as location change to conduct various activities instead of pursuing single travel purpose. This paper specifies a behavioral homogeneous person group by a job, a possession of cars. Based on this classification of person groups and their activity diary, the sequence, time and travel mode of activities in a day can be verified. As a case study household survey was conducted in city Kongju. The survey result shows that the classification of behavioral homogeneous person group based on criteria like employment status and car ownership bring a good result to forecast trip generation in traffic zone.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.193-198
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• 1999

An asymptotic distribution of the ratio of two normal vectors is estimated. Using the estimated asymptotic distribution, an approximation method to estimate confidence interval of passenger's value of travel time is proposed. As a result of empirical study the 95% confidence interval of value of travel time of home-to-work trips in city of Seoul is estimated at ￦7341.25$\pm$1945.05/hr.