• 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.

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.483-488
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• 1999

• Transportation Technology and Policy
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• v.2 no.2
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• pp.204-222
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• 2005

• Journal of Korean Society of Transportation
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• v.35 no.1
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• pp.37-49
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• 2017

This study proposes an analysis methodology for air quality improvement effect of transport and environment policy that are used for mobile pollution sources. The methodology considers the changes of traffic of road transport sources and air pollutant emission, the changes of atmospheric dispersion of air pollutants and the effects on the health of local residents in response to policy implementation. Especially, the changes to traffic flow must be considered in evaluating the effects on atmospheric environment as it has a direct connection to the effects of the policy in this study. We used bottom-up approach (BUA) based on the travel demand model to reflect the changes of travel behavior in detail in response to the policy implementation compared to the top-down approach (TDA) when calculating the changes of emission level of road transport. We showed the applicability of the proposed analysis methodology through a policy scenario analysis, and the analysis method can be effectively applied to the cases in which travelers' behavior changes are expected.

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

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.69-82
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• 2000

When new subway lines are considered to construct in a large city, there is a need to establish the appropriate transfer systems between subway and other transit modes, so as to increase the use of subway system. In this study, a multi-nominal logit model is developed to analyze the travel characteristics and the mode choice of subway Passengers transferring to and from the buses, minibuses and taxi. These passengers represent a large Portion of transit Passengers in Pusan city It shows that the explanatory variables that affect Passengers\` mode choice are in order of OVIT(Out-of-Vehicle Travel Time), IVTT(In-Vehicle Travel Time), transit fare,. income, gender, and age in modeling. In particular, OVTT is shown to have more significant impact on the mode choice than IYTT due to the fact that transfer trip is involved only in a short distance. Variables associated with the travel costs, however, do have an insignificant impact on the mode choice. It shows that it would be a better Policy to improve the quality of transit service using additional financial resource by increasing transit fare rather than by reducing the fare to increase travel demand. It also shows that value of travel time of OVTT is remarkably higher than that of IVTT and value of travel time of taxi Passengers is much higher than that of minibus Passengers .

• Journal of Korean Society of Transportation
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• v.3 no.1
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• pp.86-93
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• 1985

1965년에 출판된 고속도로용량교범(Highway Capacity Manual)은 고속도로, 도시 및 지방도로의 용량과 서비스수준을 판단하는데 기본서 역할을 해왔다. 도시내 신호등이 있는 교차로의 서비스수준은 빈하율(load factor) 개념을 이용하여 산정해 왔다. 그러나 푸른신호 주기동안 차량의 교차로이용도를 기준으로 하는 빈하율 개념은 서비스 수준의 측정치로서 한계가 있고 또 그동안 신호체계가 많이 개선되었고 운전자의 통행행태가 크게 변화하여 1970년대 중반부터 한계통행분석법(Critical Movement Analysis)과 차량의 교차로지체시간 측정법(Intersection Delay)등과 같은 새로운 기법이 소개되었다. 본 논문은 최근에 많이 이 용되고 있는 교차로지체시간측정법의 유용성을 검증하기 위해 15개 교차로의 차량통행량을 기준으로 하여 V/C비를 계산하는 한계통행분석법에 의한 측정치와 비교, 분석하였다. 그 결 과 교차로의 서비스수준을 측정하는데 양자의 방법에 의한 측정치가 크게 다르지 않음을 발 견하였다. 즉 도시내 신호등이 있는 교차로시설을 개선하기 위해 대략적인 교차로 서비스수 준을 측정할 경우 조사인원 및 비용이 많이 소요되는 한계통행분석법보다 조사가 간편하고 비용이 적게 드는 교차로지체시간측정법이 유용함을 밝혔다.

• Journal of Korean Society of Transportation
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• v.29 no.4
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• pp.7-15
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• 2011

Emerged in early 1990s, so called 'Quick service' industry that provides faster delivery of small parcels than regular mail service accelerated use of motorcycles. As the economic grows, use of large bicycles (more than 250CC displacement) for leisure purpose has also rapidly increased. Traffic crash data clearly shows the increasing trend in motorcycle crashes. The ratio of motorcycle involved crashes out of total has increased from 5.7% in 2005 to 8.3% in 2008, and similar trend can be found in fatalities ratio as well. In this study, we assess the level of risk when motorcycles operate on motorways by analyzing traffic rule violation ratio, lane change behaviour, driving speed behaviors of motorcycles in Uninterrupted Traffic Flow Facilities and using PC-CRASH simulation we also calculate car shock impulses occurred when an accident happens. Analysis result shows that the motorcycle is different from the car in terms of lane change timing and average speed, and also shows motorcycle drivers tends to conduct more improper driving behavior particularly when traffic is congested. The results from this study could be usefully applied when the law enforcement agent decides whether bicycles shall be allowed to use motorways. The result could be also utilized as fundamental information for further study of bicycles' driving behavior.

• Journal of the Korean Society for Railway
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• v.16 no.1
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• pp.59-64
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• 2013

This study analyzed passenger access and egress travel patterns related to a Korean regional railway station (Seoul station), then developed a binomial logit model. This model referred to bus and metro mode of access and egress during a national holiday (Chuseok 2009); obtained from transit smart card data. The results showed that 99% of passengers getting access to, or egress from, the regional railway station did so using less than two transfers, and that most passengers were more likely to choose a metro. However, the passengers that made access or egress trips near Seoul Station were more likely to take a bus. From the results of the mode choice model, it was found that the impact of travel time was greater than that of travel cost, in the choices made for both access and egress. Interestingly, the impact of travel time is much greater in choosing the mode of egress.

• 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.