• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2503-2508
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• 2013

Single-person households in the Seoul Metropolitan Area have increased sharply during recent 20-30 years. Despite of decreasing in the total population, the number of single-person household is predicted to increase continuously. However, the effect of single-person household growth on the domestic transport sector has not been studied concretely. In this study, the differences on trip generation characteristics by household size and attributes were figured out by analyzing Seoul Metropolitan Area Household Travel Behavior Survey (SMA-HTBS). Firstly, trip generation rates (trips/day/person) were produced by household attribute, household member attribute and trip attribute based on SMA-HTBS. Secondly, trip generation rate of single-person household and that of multi-person (2 or more) household were compared by significance test. It was found that trips generation characteristics of single-person household is quite different from those of multi-person household by housing type, residential type, living area, and transport mode. The result of this paper is expected to contribute developing more sophisticated trip generation model and transport policy reflecting trip generation characteristics of single-person household.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5D
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• pp.657-662
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• 2011

The relationship between household attributes and trip generation can only be found in Seoul Metropolitan Household Travel Survey, which has been implemented every 5 years. However, various household attributes' impact on trip generation has not been analyzed closely. This paper compared and analyzed those impact. The results could be useful when trip generation models are studied in the future. They are as follows. The household size should be an important classification criteria when household trip generation is estimated. The traditional assumption that the relationship between household auto ownership and trip generation is positive and linear correlation should be reconsidered. Weekday travel data only did not showed that housing type has an influence on trip generation. Household income is unrelated with trip generation among single-person household, while multi-person household is related strongly. However, when trips are classified by purpose, impact of household income on trip generation are varied by trip purpose. Especially, the increase in single-person household can not be overlooked when trip generation is forecasted.

• Journal of Korean Society of Transportation
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• v.14 no.4
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• pp.31-48
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• 1996

This paper develops a disaggregate model system for travel behavior of workers in a metropolitan area. We attempt to develop a set of models for predicting trip generation type, trip purpose, destination, mode choices in each trip on the way from work to home by using the concept of utility maximization of base-to-base tour. The model incorporates the concept that decisions of a trip in a trip in a travel tour depend on decisions of the trips having been made before and decisions of trip planned after of this trip, as well as on current trip conditions. As the structure of the model, the nested logit model is used to avoid a simultaneous model's complexity. The data to be used for estimating the model system are from the person trip survey which was carried out in 1981 in Nagoya metropolitan. Empirical tests of the model for Nagoya metropolitan area show encouraging results and prove the validity of the assumption of this model.

• Journal of Korean Society of Transportation
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• v.17 no.5
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• pp.7-18
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• 1999

This Paper focuses on analyzing the influences of Teleservice on travel behavior and trip demand based on the individual behavior model. The first step is to classify individuals into different Person groups who will follow similar behavior Patterns in terms of travel and communication. And then, the effect of Teleservice on trip demand is estimated using hypothetical scenario. The results on the ability of each person group to adapt themselves to Teleservice show that full-time housekeepers and senior citizens are more likely to be alienated. It is also found that transition probability to Teleservice is high for activities in bank or public office where simple forms of information such as data or text are exchanged. On that basis, it is estimated that in Seoul the savings on trip demand by Teleservice will be 7.6% of total daily trip generations.

• 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.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• The Journal of Bigdata
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• v.5 no.2
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• pp.85-95
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• 2020

In this study, a mobility analysis method is suggested to estimate an O/D trip demand estimation using Mobile Phone Signaling Data. Using mobile data based on mobile base station location information, a trip chain database was established for each person and daily traffic patterns were analyzed. In addition, a new algorithm was developed to determine the traffic characteristics of their mobilities. To correct the ping pong handover problem of communication data itself, the methodology was developed and the criteria for stay time was set to distinguish pass by between stay within the influence area. The big-data based method is applied to analyze the mobility pattern in inter-regional trip and intra-regional trip in both of an urban area and a rural city. When comparing it with the results with traditional methods, it seems that the new methodology has a possibility to be applied to the national survey projects in the future.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.507-517
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• 2018

This study is focused on analyzing the characteristics of repeat foreign tourists to Korea and suggest how to increase the repeat ratio. As the result of analysis, there were significant differences in the variables of sex, age, country in the case of demographic characteristics and in the variables of travel types, the number of company, the purpose of visit, accommodations, major visiting places and visiting areas in the case of travel characteristic. And also there were significant differences in the variables of accommodation fees per person and expenses per person in their own country in the case of travel expenses and in the variables of immigration formalities, public transportations, accommodations, foods, shopping, tourist attractions and security in the case of satisfaction. Lastly there were significant differences in the variables of revisit intention within 3 years, recommendation intention, the image of Korea(before trip) and the image of Korea(after trip) in the case of behavior intention after trip and image evaluation. Therefore it should be considered the characteristics of repeat foreign tourists when we make the tourism products to increase the repeat ratio.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.417-424
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• 2006

To get more accurate trip distribution estimation results, this study developed an improved gravity model. Using three different year's O-D table resulted from person trip survey, this study analyzed correlative between basic year's residuals and target year's residuals by gravity model. And resulted that the two have linear correlation. From this, improved gravity model was developed as adding basic year's residual to present gravity model. Developed gravity model was compared to present gravity model by estimation accuracy, and revealed that distributed trips from improved gravity model was more closer to real O-D than distributed trips from present gravity model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.119-137
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• 2020

Over the last two decades, the attitudes to cars have changed from buying a car to sharing a car, especially among young people. Shared transport services and autonomous vehicles together can resolve the accessibility issue of shared transport services. Furthermore, they will make it possible to develop a new model of apartments without car parking. Therefore, the study estimated the demand for car sharing by young people and the running efficiency of car-sharing dealing with their car-based trip demand. The study chose nine apartment complexes for study sites where a majority of the residents were young people. The questionnaire survey was conducted to collect data on the trip demands of young people. The results showed that there are significant differences in the car-sharing use patterns and demand between the apartment houses located in the Capital region and non-capital region. Young people living in apartments in the Capital region used car sharing once per day per person for approximately 80 minutes per trip and tended to hire that between 8 AM and 10 AM. On the other hand, the young people living in apartments in the non-capital region used car sharing twice per day per person for approximately 200 minutes per trip. They tended to hire that frequently in the afternoon and evening as well as in the morning. The results also showed that a single car-sharing vehicle could deal with 3~4 trips per day in the Capital region and around 2 trips per day in the non-capital region.