• Journal of the Korean Geographical Society
• /
• v.32 no.2
• /
• pp.217-228
• /
• 1997

A Study on individual Characteristics and Daily Activities of Housewives in the City of Kwangju. This study examines housewives' daily activities, focusing upon individual characteristics. The data used in this study are based on the fuestionaire survey, asking of personal trip for the weekdays and the weekend. Daily activities are classified into 7 categories and individual characteristics are revealed by age, occupation, a degree of education, number of family, and the residential environment. The results of this study are as follows: 1) The relations between daily activities and individual characteristics are influenced by housewife's occupation. Daily activities of housewives who have jobs are different from those who do not have jobs for a weekday as well as for a weekend. 2) Housewives' daily activities show very busy and vigorous on Saturday. 3) Housewives who are employed are willing to make mutipurpose trips on Saturday. 4) For a weekday, housewives' daily activities are inclined to make one cycle trip in a day, and the more trip cycles are, the more multipurpose trips are made. 5) The relationships between daily activities and individual characteristics show the pattern of WH, WLH, LHLH as it can be grouped.

• Journal of Korean Society of Transportation
• /
• v.20 no.6
• /
• pp.129-140
• /
• 2002

This paper develops a dynamic structural equation model, which captures relationships among socio-demographics, activity participation(i.e., time use) and travel behavior in consideration with time variation effects. The data used in developing the model are two waves(the year 1991 and 1992) from Puget Sound Transportation Panel (PSTP). which is surveyed in Puget Sound Region in United States. The PSTP is widely used in transportation behavior analysis and includes various information of traveler's socio-economic, travel patterns, and activity participation. In the model, we use 10 endogenous variables including activity participations and travel behaviors and 10 exogenous variables composed of time variant and invariant traveler's socio-demographic variables. The empirical model shows that strong relationships exist not only between socio-demographics and travel behavior, but between waves. We also confirm needs of panel data set to identify and understand time variation effects and travel behaviors.

• Journal of Korean Society of Transportation
• /
• v.8 no.1
• /
• pp.89-102
• /
• 1990

본 연구에서는 개별모형(disaggregate model)을 이용한 도시권의 교통수요예측 모형체계의 구축을 최종목적으로 하며, 그때 개인이 1일 중에 행하는 복수의 트립에 관한 의사결정간의 상호관계를 적절히 고려함에 의해, 되도록 개인의 교통행동을 논리적으로 설명함과 동시에 모형의 취급이 용이하도록 논리성과 실용성이 잘 조화된 모형의 구축을 시도하였다. 모형의 체계는 비취업자와 취업자 각각의 1일의 통행행태유형의 선택에 관한 2개의 Sub-model로 구성되어져 있다. 본 논문은 그 Sub-model중의 하나인 비취업자의 1일의 통행행태유형(트립발생, 각 트립의 목적지와 교통수단)의 선택에 관한 개별모형의 개발을 행한 것이다. 본 모형의 특징은 tour별 효용최대화행동가설에 기초를 두어 개인이 1일 중에 행하는 각 트립의 선택행동은 해당트립의 전후에 행해지는 트립들의 선택행동의 영향을 고려하여 의사결정을 하는 것으로 가설을 설정하여 트립간의 상호관련성을 표현하였다. 모형의 구조로서는, 모형의 취급이 보다 용이하도록 tour별 효과최대화를 트립단위의 단계형 모형으로 표현하는 nested logit model형의 수차동시효과최대화 모형을 구축하였다 실제의 도시권에 대한 실증적 검토를 행한 결과, 본 연구에서 개발한 별개모형의 유효성이 확인되었다.

• Journal of Korean Society of Transportation
• /
• v.20 no.7
• /
• pp.79-85
• /
• 2002

In this paper, multilevel models are adopted to identify interactions among household members in trip making behaviors. The multilevel approach is a proper methodology to handle samples, which are extracted from a hierarchical structure universe. PSTP dataset is used in developing models and understand proportion of variations among individuals and household. The results of this study show that for activity participation and travel behavior household level variance is more than 1/4 of person level variance and therefore not negligible. The results confirm the importance of multilevel model in travel behavior analysis.

• Environmental and Resource Economics Review
• /
• v.30 no.2
• /
• pp.207-235
• /
• 2021

This paper examines the effects of ambient air pollution by ozone and particulate matter on traveling by mode of transport. We estimate the SUR model of travel time by different modes of transportation using individual level data of travel diaries. We find that, as air pollution levels rises, traveling by privately-owned vehicles increases but traveling by bus decreases. Our results also show that, when an air quality alert is issued, bus traveling increases in an effort to reduce pollution levels, but traveling by own car does not change and traveling by train declines. This suggests that alert programs may not be highly effective in reducing air pollution emissions from vehicles because voluntary switching to public transportation induced by air quality alerts is outweighed by individual effort of avoiding exposure to pollution.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.15 no.2
• /
• pp.50-62
• /
• 2016

With programmable applications that utilize sensors, such as global positioning systems and accelerometers, smartphones provide an unprecedented opportunity to collect behavioral data in an unobtrusive and cost-effective manner. This paper assesses the relative accuracy and reliability of the Future Mobility Sensing (FMS), a smartphone-based prompted-recall travel survey. We compared the data extracted from FMS with the data collected from the Korea Passenger Trip Survey (PTS), a traditional self-reported, paper-based travel survey. In total, 46 undergraduate students completed the PTS for seven consecutive days, while also carrying their smartphones with the activated FMS applications for the same time span. After completing the PTS, the participants validated their FMS data on the web-based prompted recall surveys. We then matched the validated FMS data with the PTS-based records. The FMS turns out to be superior in detecting short trips, which are usually under-reported in self-reported travel surveys. The reported PTS travel times are longer than for the FMS, suggesting that participants tend to overestimate their travel time in the PTS. This study contributes to the ongoing development of smartphone-based travel behavior data collecting methods.

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

• Proceedings of the KOR-KST Conference
• /
• 1998.10b
• /
• pp.261-261
• /
• 1998

교통계획의 목적은 교통체계를 분석하여 교통과 활동간의 상호작용을 효율화시켜 도시 및 지역사회의 목표를 달성하는데 있으며, 합리적인 교통계획을 수립하여 한정된 투자재원을 효율적으로 배분하기 위해서는 교통수요에 대한 합리적 접근이 필요하다. 교통수요예측의 접근방법은 미시적인 개별적 접근방법과 거시적인 집단적 접근방법으로 구분되며, 다시 모형화 기법이 결정적인가 확률적인가에 따라 개별결정적, 개별활률적, 그리고 집단결정적, 집단확률적 모형의 4가지로 구분될 수 있다. 이 중에서 일반적으로 관심의 대상이 되는 2가지 형태는 집단결정적, 개발확률적 모형이다. 집단결정적모형은 전통적 교통수요예측모형에 해당되며, 개별확률적모형은 1970년대 Mc Fadden을 시작으로 Ben-Akiva, Manheim을 중심으로 한 소비자 행동선택 이론에 근거한 개별행태모형이 이에 해당된다. 개별행태모형은 개개인의 통행행태를 다른 모든 조건이 동일할 때 개개인은 비용의 최소화를 추구하고, 비용과 관련한 통행행태는 거시적 수준에서의 주어진 제약 조건과 관계가 있으며, 의사결정은 확률분포에 의해서 결정되는 효용원칙(Efficiency Principle)에 입각하여 해석한다. 도시내와 도시간, 취업자와 비취업자, 출퇴근 시, 목적별 등의 여러 가지 통행에 있어서 다양한 변수들을 사용하여 교통수단 선택모형의 파라메카 값을 추정하고 통행패턴을 분석해 왔다. 본 논문에서는 개별행태모형인 로짓모형 중에서 집단다항로짓모형을 이용하여 여러 통행 중 공항시설의 접근에 필요한 교통수단 효용함수의 파라메타 값 추정 시, 일반적으로 사용되는 통행시간, 통행비용이라는 변수를 공통으로 두고, 대중교통의 경우에만 해당하는 환승이라는 특정대안변수(Specific alternative variable)를 첨가하여 그것이 수단선택에 미치는 영향을 분석한다. 또한, 대중교통의 속성을 가지고 있는 지하철과 버스를 하나의 대안으로 묶어서 효용함수를 구한 다음 다시 승용차, 택시, 대중교통을 독립된 대안으로 두고 모형을 정립하는 NESTED LOGIT모형으로 파라메타를 추정하여 대중교통의 효용에 관해 분석·비교하였다. 본 논문에 이용된 자료는 공항을 이용하는 이용객들을 대상으로 직접 설문·면접조사한 자료이며 대상 교통수단은 승용차, 택시, 지하철, 버스로 설정하였다.

• Journal of Korean Society of Transportation
• /
• v.21 no.4
• /
• pp.145-154
• /
• 2003

Multilevel and Multivariate Structural Equation Mpdel is applied to handle the hierarchical nature of the data and explain complex relationship among socioeconomic factors of individuals and household, activity participation, and travel behavior using Puset Sound Transportation Panel data. From analysis, variations of individual activity participation and travel behavior can be divided into two categories : Within-household variation and Between-households variation. Empirical results show that the interdependency index(p) of variables for household members within a household is between 0.13 and 0.33 indicating high interdependency. These results suggest that Multilevel and Multivariate SEM approach is an appropriate modeling methodology and gives additional information for activity participation and travel behavior. Also most of personal and household characteristics influence on activity participation and travel behavior within a household as well as between households.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.35 no.5
• /
• pp.1103-1110
• /
• 2015

Ratio of a day's tour for Geoje-si, 22.6 percent, has increased to 48.6 percent since the opening of Busan-Geoje fixed link. Eight cities of Yeungnam area including Busan-Ulsan and Daegu-Gyeongbuk has been directly affected by the changed route from GJ Bridge to BG Bridge. In order to compare the range of departure area for a one-day trip in Geoje tourist attractions before and after the new fixed link, duration variation of visitors is described as individual difference by normal distribution function. One-day tour trip model based on a circular trip is also suggested under comparatively simple supposition. Since average area after the opening is equal to maximum area before as minimum area after is equal to average area before, the effect of access improvement by the new bridge is revealed definitely. In addition, the effect of cities located in the middle and long distance is greater. Although cities proximity to Geoje are not influenced significantly, every citizen is capable of taking a one-day trip anywhere.