• Journal of Korean Society of Transportation
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• v.19 no.2
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• pp.43-52
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• 2001

대부분의 관측교통량기반 수요추정기법은 소규모 및 중규모 교통망 등의 상대적으로 규모가 작은 교통망에서 기본적으로 가정된 수요를 가지고 얻은 추정O/D를 기본O/D와 비교하여 그 추정의 정확성이 어느 정도인가를 오차분석법 등을 이용하여 비교.분석하는 것이 그 주요한 분석방향이라고 할 수 있었다. 이러한 접근법은 실제 현실에서는 알 수 없는 참O/D나 참관측교통량을 가정하고 제시된 모형을 면밀히 관찰하여 모형의 장단점이 무엇인지를 파악하거나 타모형과의 비교.분석을 용이하게 하고자 할 때 많이 이용된다. 그러나 이러한 가정된 교통망이나 참O/D(true O/D) 등은 모형의 적용가능성을 살필 경우에 이용 가능한 방법이라고 할 수 있지만, 참O/D를 알지 못하는 현실상황(대규모 교통망)에서는 추정O/D의 신뢰성을 평가하기란 매우 힘든 작업이거나 거의 불가능한 일이라 할 수 있다. 이러한 문제점을 보완하고자 본 연구에서는 서울시의 1996년도 교통센서스 자료를 이용하여 가정된 수요가 아닌 실제적이고 현실적인 자료를 가지고 대규모 교통망에서 이용될 수 있는 모형을 살펴보았다. 연구방법은 대규모 교통망에 기존의 단일차종기반모형과 본 연구에서 제시한 다차종(multiclass)기반모형을 적용하여 추정된 O/D에 TLFD(Trip Length Frequency Distribution)개념을 이용하여 추정된 O/D의 신뢰성을 평가하고자 하였다. 또한, $R^2$를 이용하여 모형 적용 전후의 관측교통량과 배분교통량을 비교하여 추정력을 분석하였다. 본 연구에서는 단일차종기반모형보다는 차종간 혼잡효과 및 노선선택비율을 차종별로 감안할 수 있는 다차종기반모형이 대규모교통망에서는 보다 적절한 결과를 나타내는 것으로 분석되었다.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.101-111
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• 2005

Various urban transport policies have an effect on urban transit riderships and accessibility. This study reports variations of metropolitan subway travel patterns affected by an enormous change in bus routes and transfer discount fare policy between subway and bus mode conducted by Seoul city in July 1st of 2004. In an effort to see the difference between the before and the after policies, two data sets are prepared. Firstly, on a daily bassis. an origin-destination trip table of May of 2004 is used. Secondly, on a daily bassis, an origin-destination trip table of August-September of 2004 is used as a counter measure. Even if seasonal variation was not considered, Seoul metropolitan area have experienced increasing riderships and accessibility. Finally, the effects of accessibility in spatial interaction model by rall service changes such as random shocks were scrutinized and interpreted in detail.

• Journal of Korean Society of Transportation
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• v.26 no.3
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• pp.199-209
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• 2008

This paper is described the concepts and limitations for the traditional directional design hour volume estimation. The main objective of this paper is to establish an estimation method of probabilistic directional design hour volume in order to improve the limitation for the traditional approach method. To express the traffic congestion of specific road segment, this paper proposed the link travel time as the probability that the road capacity can accommodate a certain traffic demand at desired service level. Also, the link travel time threshold was derived from chance-constrained stochastic model. Such successive probabilistic process could determine optimal ranked design hour volume and directional design hour volume. Therefore, the probabilistic directional design hour volume can consider the traffic congestion and economic aspect in road planning and design stage. It is hoped that this study will provide a better understanding of various issues involved in the short term prediction of directional design hourly volume on different types of roads.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.1
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• pp.59-77
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• 2008

The purpose of this study is to investigate the impact of traffic-related air pollution on the urban population in the Metropolitan Seoul area. In particular, this study analyzes urban population exposure to traffic-related particulate materials(PM). For the purpose, this study examines the relationships between traffic flows and PM concentration levels during the last fifteen years. Traffic volumes have been decreased significantly in recent year in Seoul, however, PM levels have been declined less compare to traffic volumes. It may be related with the rapid growth in the population and vehicle numbers in Gyenggi, the outskirt of Seoul, where several New Towns have been developed in the middle of 1990's. The spatial pattern of commuting has changed, and thus and travel distances and traffic volumes have increased along the main roads connecting CBDs in Seoul and New Towns consisting of large residential apartment complexes. These changes in traffic flows and travel behaviors cause increasing exposure to traffic-related air pollution for urban population over the Metropolitan Seoul area. GIS techniques are applied to analyze the spatial patterns of traffic flows, population distributions, PM distributions, and passenger flows comprehensively. This study also analyzes real time base traffic flow data and passenger flow data obtained from T-card transaction database applying data mining techniques. This study also attempts to develop a space-time model for assessing journey-time exposure to traffic related air pollutants based on travel passenger frequency distribution function. The results of this study can be used for the implications for sustainable transport systems, public health and transportation policy by reducing urban air pollution and road traffics in the Metropolitan Seoul area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.1-11
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• 2009

TCS Data imply characteristics of traffic conditions. However, there are outliers in TCS data, which can not represent the travel time of the pertinent section, if these outliers are not eliminated, travel time may be distorted owing to these outliers. Various travel time can be distributed under the same section and time because the variation of the travel time is increase as the section distance is increase, which make difficult to calculate the representative of travel time. Accordingly, it is important to grasp travel time characteristics in order to compute the representative of travel time using TCS Data. In this study, after analyzing the variation ratio of the travel time according to the link distance and the level of congestion, the outlier elimination model and the smoothing model for TCS data were proposed. The results show that the proposed model can be utilized for estimating a reliable travel time for a long-distance path in which there are a variation of travel times from the same departure time, the intervals are large and the change in the representative travel time is irregular for a short period.

• Journal of Korean Society of Transportation
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• v.13 no.2
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• pp.19-42
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• 1995

1980년대 후기부터 교통정책의 우선 목표는 지역경제성장 자체가 교통문제를 스스로 해결할 수 있도록 하기 위하여 종래의 관리 중시의 정책은 다시 토지이용 정책으로 변화를 초래하엿다. 오늘날 대도시는 개개 졍제활동 주체들의 동적인 경제 행태에근거하여 분산구조를 띠고 있다. 이러한 동적인 경제행태에 미치는 요소들은 교통체계와 토지이용과 상호연관성의 연구에 필수적인 지가, 인구분포, 통행행태등이다. 그러나 전통적인 단핵도시 모형은 대도시의 분산구조형태의 동적인 과정을 설명하는데는 한계가 있다. 본 연구는 대도시의 변천과정을-도심 및 부심의 출현·소멸현상-설명함으로써 도시교통정책 필수적인 입지와 통행패턴에 대한 새로운 동태적 이론의 기초를 제공하는데 그 목적이 있다. 이를 위하여 지역경제 성장과 도시공간구조와의 동태적관계를 통합하는 토지이용과 교통의 연속 모형을 개발·응용하였다. 개발된 모형에서는 교통량에 따른 교통비용, 도시공간구조로 인한 외부효과들, 경제활동주체들의 비동질성, 이주비용, 그리고 집적 이익등이 매기마다 내생적으로 결정되어 대도시의 공간구조 변화를 설명한다. 경제 호라동주체들간의 ? 호물리적 교류는 소득 증대에 의하여 경제구조가 변함에 따라 새로이 결정된다. 가상적 도시와 자료를 가지고 실험한 결과 비동질적인 경제주체들의 불균형적 성장이 장기적으로 도시구조에 영향을 미치며, 기본적인 경제행위에 따라 장기동태적인 과정을 통하여나타나는 도시의 분산구조형태의 중요성을 보여주고 있다. 또한 교통비용의 변화에 따른 민감도분석을 통하여 모형의 실용성을 검정하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.1115-1122
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• 2013

Recently the demands for traffic information tend to increase, and travel time might one of the most important traffic information. To effectively estimate exact travel time, highly reliable traffic data collection is required. BIS(Bus Information System) data would be useful for the estimation of the route travel time because BIS is collecting data for the bus travel time on the main road of the city on real-time basis. Traditionally use of BIS data has been limited to the realm of bus operating but it has not been used for a variety of traffic categories. Therefore, this study estimates a route travel time on road networks in urban areas on the basis of real-time data of BIS and then eventually constructs regression models. These models use an explanatory variable that corresponds to bus travel time excluding service time at the bus stop. The results show that the coefficient of determination for the constructed regression model is more than 0.950. As a result of T-test performance with assistance from collected data and estimated model values, it is likely that the model is statistically significant with a confidence level of 95%. It is generally found that the estimation for the exact travel time on real-time basis is plausible if the BIS data is used.

• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.113-122
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• 2008

This study extended Park et al.(2007c), which analyzed the efficiency of a hierarchical transit network, showed the result of a real data, and analyzed its applicability. Operating cost was estimated using a model which was established in this study, and minimum transit demand was derived from the operating cost. The minimum transit demand value is just a sample calculation, thus it varies by many inside and outside factors of the model. Looking at the inside of the model, operating cost and travel speed are major factors, and the possibility of introducing urban subway becomes high when the operating cost of the transit system is low and its travel speed is high. As far as the outside factors are concerned, according to the analysis on the network structure, transit demand, and transit mode share, the minimum transit demand value which was derived in this study will be the maximum value among the possible values. In the feasibility study, the benefit is likely to be overestimated and the cost is likely to be underestimated than those of this study. It could be concluded that the methodology of a feasibility study is appropriate in the field standard. This study analyzed the efficiency of introduction of urban subway using analytical approach, thus has many shortcomings and limitations. However the practical approach, like feasibility study, has some limitations as well. This study could be a basis on establishing an analysis framework that is more accurate and reasonable by comparing analytical approach and practical approach.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.58-82
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• 1995

This study providesd an empirical analysis of trip-chaining behavior and its application to transportation planning. In the empirical analysis, changes in trip-chaining patterns since 1970 have been examined and details of current trip-chaining behavior as they describe shopping trip-chaining behavior has changed. Individual trip-chaining has become longer and complex. It appears that the average number of trips per chains has substantially increased over the past 20 years. An increased number of trips in chains means fewer home-based trips. Changes in trip-chaining behavior have several consequences. Important consequences are for transportation and land-use planning. Up to now trips have been treated as if they are independent clusters of home-to-destination-to-home; this approach has not usually taken into account the trip-chaining behavior of individuals. this calls for a different approach to at least the trip generation and trip distribution part of transportation planning. In this study, application of trip-chaining behavior to trip distribution model formulation is proposed and its calibration results are presented.

• 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.