• Title/Summary/Keyword: household travel survey

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A Study on the Factors Concerning Non-Work Trip of the Elderly People : A case of Seoul Metropolitan Area (고령자의 비업무통행에 영향을 미치는 요인 분석: 수도권 사례를 중심으로)

  • Hahn, Jin-Seok;Oh, Sung-Ho;Park, Jong-Il;Kim, Joon-ki
    • Journal of Korean Society of Transportation
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    • v.30 no.4
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    • pp.61-70
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    • 2012
  • This research explores different non-work trip characteristics between the elderly group (65+) and the working age group (20-64) using heteroscadastic ordered logit model. The analysis is based on travel survey data of Seoul Metropolitan area in 2006. The results show that age induces heteroscadasticity and the model provides a better fit than ordered logit model. The factors increasing the number of non-work trip of the elderly were driver's license and household income. Conversely, the number of non-work trips decreased in those groups that were male, with a job, in aging, and with the number of preschool children. The factors having opposite effects (increased the number of non-work trips in the working age groups and decreased in the elderly group) between the elderly group and working age group were age and job.

Effects of Compact City Development on Residents' Shopping Trips -A Case study of Seoul (압축도시 계획요소가 지역주민들의 쇼핑통행에 미치는 영향 -서울시를 대상으로)

  • Ko, Eunjeong;Lee, Kyunghwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.8
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    • pp.4077-4085
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    • 2013
  • The purpose of this study is to analyze relationships between compact city development and residents' shopping trips in Seoul. Compact city planning factors are classified into land use and traffic environment. The main data source used for this research is 2006 Household Travel Survey data, then a statistic analysis was carried out by applying random intercept logit model. Analysis shows that a high level of residential density increases residents' local shopping. Also, a high level of residential density and land use mix results in more uses of public transportation, bicycle and walking for shopping. Also, more access to public transportation leads to more use of public transportation for shopping. Therefore, compact city development will have a positive impact on activating the use of public transportation, bicycle and walking for shopping.

Impacts of Neighborhood's Land Use and Transit Accessibility on Residents' Commuting Trips - A Case study of Seoul (근린의 토지이용과 대중교통시설 보행접근성이 통근통행에 미치는 영향 - 서울시를 대상으로)

  • Lee, Kyunghwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.9
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    • pp.4593-4601
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    • 2013
  • The purpose of this study is to analyze neighborhood's land use and transit accessibility affecting residents' commuting trips through a case study of Seoul. The main data source used for this research is 2010 Household Travel Survey data from which 34,071 observations were selected as the final sample. Then a statistic analysis was carried out by applying random intercept logit model. Analysis shows that a high level of residential density, land use mix in neighborhood results in more use of subway for commuting. And higher access to subway station leads to more use of subway. Therefore, a high dense and mixed use development as well as a high accessibility to transit station can contribute to activating the use of public transportation for commuting. Finally, the walking range of subway station affecting transit mode for commuting is estimated at between 432 to 525m.

Influence of COVID-19 on Public Transportation Mode Change and Countermeasures (COVID-19에 따른 대중교통수단 변화에 미치는 영향 분석 및 대책에 관한 연구)

  • Kim, Su Min;Jung, Hun Young
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.3
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    • pp.379-389
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    • 2022
  • The number of public transportation users has dropped drastically due to COVID-19. In this work, my survey was conducted to uncover the factors that influence citizens' travel patterns. Data were collected and logistic regression analysis on the shifts in transportation was undertaken. Additionally, an importance-performance analysis was carried out to investigate how to effectively operate public transportation systems and improve facilities. The main research findings were as follows: First, the more individuals were concerned about COVID-19 (+) and being infected when using public transportation (+), the greater the tendency to switch to private transportation modes. Secondly, when it came to personal traits, respondents who could drive a car (+) or owned a car (+)or did more online shopping (+) or used public transportation for trips (+) tended to switch over, compared with respondents who could not drive or did not own a caror used public transportation to commute. In addition, respondents who were vaccinated (-) or had more household members tended not to switch transportation modes, compared with those who were not vaccinated or had fewer household members. Third, it is important to continue the following efforts to safeguardhygiene linked to public transportation: wearing masks, disinfecting hands, controlling diseases, and general cleaning. The conclusion was that it is important to put traffic congestion and ventilation issues first, especially in regards public transportation, which was not rated as satisfactory enough compared to its importance. The research findings can provide useful basic data when establishing countermeasures to the current COVID-19 circumstances in the areas of public transportation operation and management and in the event of an infectious disease outbreak in the future.

Commuting Efficiency Comparison of Metropolitan Areas in South Korea: Application of Constrained Monte-Carlo Simulation to Avoid the MAUP (우리나라 대도시권 통근 효율성 비교: MAUP 회피를 위한 Constrained Monte-Carlo Simulation의 활용)

  • Hyunseong Yun;Seung-Nam Kim
    • Land and Housing Review
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    • v.15 no.2
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    • pp.73-87
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    • 2024
  • To evaluate the efficiency of commuting patterns, various commuting indicators such as excess commute and commuting potential utilized have been developed and used. It is crucial to calculate these indicators reasonably to reveal the differences in commuting patterns among metropolitan areas and to consider these in the process of formulating commuting policies. However, commuting indicators are generally calculated at the administrative district level, and thus, they are not free from the problem of the modifiable areal unit problem (MAUP). This issue can undermine the rationality of comparing commuting efficiency between metropolitan areas, making it necessary to handle the calculation of commuting indicators carefully. Therefore, this study utilises Monte Carlo Simulation to calculate optimal, actual, and maximum commuting distances, and thereby presents the excess commute and the commuting potential utilized. To apply Monte Carlo Simulation to the context of South Korea, a constrained Monte Carlo Simulation is conducted, where residential and workplace locations used in the simulation are selected based on the actual locations of buildings. The analysis is conducted on 13 metropolitan areas with established metropolitan plans using the 2016 Household Travel Survey data. The commuting indicators calculated through the simulation showed minimal differences compared to the results obtained through conventional methods. The comparison of commuting efficiency among metropolitan areas revealed that even if the degree of spafial balance between residential and workplace locations is similar, the actual commuting patterns can differ significantly. It is suggested that further research considering characteristics such as the area of each metropolitan region will be necessary in the future.

The Estimation Model of an Origin-Destination Matrix from Traffic Counts Using a Conjugate Gradient Method (Conjugate Gradient 기법을 이용한 관측교통량 기반 기종점 OD행렬 추정 모형 개발)

  • Lee, Heon-Ju;Lee, Seung-Jae
    • Journal of Korean Society of Transportation
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    • v.22 no.1 s.72
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    • pp.43-62
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    • 2004
  • Conventionally the estimation method of the origin-destination Matrix has been developed by implementing the expansion of sampled data obtained from roadside interview and household travel survey. In the survey process, the bigger the sample size is, the higher the level of limitation, due to taking time for an error test for a cost and a time. Estimating the O-D matrix from observed traffic count data has been applied as methods of over-coming this limitation, and a gradient model is known as one of the most popular techniques. However, in case of the gradient model, although it may be capable of minimizing the error between the observed and estimated traffic volumes, a prior O-D matrix structure cannot maintained exactly. That is to say, unwanted changes may be occurred. For this reason, this study adopts a conjugate gradient algorithm to take into account two factors: estimation of the O-D matrix from the conjugate gradient algorithm while reflecting the prior O-D matrix structure maintained. This development of the O-D matrix estimation model is to minimize the error between observed and estimated traffic volumes. This study validates the model using the simple network, and then applies it to a large scale network. There are several findings through the tests. First, as the consequence of consistency, it is apparent that the upper level of this model plays a key role by the internal relationship with lower level. Secondly, as the respect of estimation precision, the estimation error is lied within the tolerance interval. Furthermore, the structure of the estimated O-D matrix has not changed too much, and even still has conserved some attributes.