• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.81-99
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• 2020

Origin-destination data have been collected and utilized for demand analysis and service design in various fields such as public transportation and traffic operation. As the utilization of big data becomes important, there are increasing needs to store raw origin-destination data for big data analysis. However, it is not practical to store and analyze the raw data for a long period of time since the size of the data increases by the power of the number of the collection points. To overcome this storage limitation and long-period pattern analysis, this study proposes a methodology for compression and origin-destination data analysis with the compressed data. The proposed methodology is applied to public transit data of Sejong and Seoul. We first measure the reconstruction error and the data size for each truncated matrix. Then, to determine a range of principal components for removing random data, we measure the level of the regularity based on covariance coefficients of the demand data reconstructed with each range of principal components. Based on the distribution of the covariance coefficients, we found the range of principal components that covers the regular demand. The ranges are determined as 1~60 and 1~80 for Sejong and Seoul respectively.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.159-160
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• 2016

본 연구는 우리나라 수출입 컨테이너화물의 5대 내륙기종점 권역별로 항만집중도 및 변이효과를 분석함으로써, 항만간 경쟁 구도 및 효율적인 컨테이너부두 개발 및 운영에 대한 시사점을 도출하고자 한다. 2011년, 2006년, 2011년의 항만별 내륙기종점 조사자료를 바탕으로 허쉬만-허펜달지수 및 변이할당법을 활용하여 분석하였다.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.57-66
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• 2004

When we estimate an origin-destination matrix from traffic counts. origin-destination matrix estimation from traffic counts according to the selected optimal traffic counting links is method for improving the results of origin-destinaation matrix estimation and for increasing economic efficiency. This paper proposed model of selecting traffic counting links using integer program technique, and selected a traffic counting links using this model, and estimated and origin-destingtion matrix from traffic counts according to the selected optimal traffic counting links. Also, we compared a result of estimating origin-destination matrix from the selected optimal traffic counting links using this model to a result of estimating origin-destination matrix from the randomly selected traffic counting links. The error analysis result was more improved a result of origin-destination matrix estimation using this model than a result of randomly selected links.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.219-232
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• 2023

Mobility services need to change according to the regional characteristics of the target service area. Accordingly, analysis of mobility patterns and characteristics based on Origin-Destination (OD) data that reflect travel behaviors in the target service area is required. However, since conventional methods construct the OD data obtained from the administrative district-based zone system, it is hard to ensure spatial homogeneity. Hence, there are limitations in analyzing the inherent travel patterns of each mobility service, particularly for new mobility service like Demand Responsive Transit (DRT). Unlike the conventional approach, this study applies a data-driven clustering technique to conduct spatial analyses on OD travel patterns of regional mobility services based on reconstructed OD data derived from re-aggregation for original OD distributions. Based on the reconstructed OD data that contains information on the inherent feature vectors of the original OD data, the proposed method enables analysis of the spatial characteristics of regional mobility services, including public transit bus, taxi and DRT.

• Proceedings of the KOR-KST Conference
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• 2002.02a
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• pp.45-77
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• 2002

교통혼잡 문제가 점점 심각해짐에 따라 대중교통의 중요성은 날로 부각되며, 대중교통을 지원하기 위한 정책들이 속속 입안되고 있어 대중교통을 심도 있게 분석할 수 있는 틀의 개발은 필연적이라 할 수 있다. 이에 본 연구는 대중교통 통행배정모형 개발과 대중교통 기종점통행량(OD) 추정을 목적으로 수행되었다. 대중교통 통행배정모형의 개발부분에서는 기존의 대중교통 통행배정모형이 개별차량과 다른 대중교통의 특성을 정확히 반영하고 있지 못하다는 한계를 극복하고자, 최적경로 탐색에는 유전자 알고리즘(Genetic Algorithm)을 통행량 배정에는 로짓모형을 기반으로 한 확률적 통행량 배정모형(Stochastic Network Loading Model)을 이용하여 TATSN 모형을 개발하였다. 그리고, 대중교통 기종점통행량의 추정은 전통적인 기종점통행량 추정 방법인 기종점조사 방법이 시간과 비용이 과대하게 소요된다는 단점을 인식하여 관측통행량을 이용하여 추정하는 방법을 제안하였다.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.129-137
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• 2009

Operation of intelligent transport systems technologies in transportation networks and more detailed analysis give rise to necessity of dynamic traffic analysis model. Existing static models describe network state in average. on the contrary, dynamic traffic analysis model can describe the time-dependent network state. In this study, a dynamic traffic model for the expressway system using FTMS data is developed. Time-dependent origin-destination trip tables for nationwide expressway network are constructed using TCS data. Computation complexity is critical issue in modeling nationwide network for dynamic simulation. A subarea analysis model is developed which converts the nationwide O-D trip tables into subarea O-D trip tables. The applicability of the proposed model is tested under various scenario. This study can be viewed as a starting point of developing deployable dynamic traffic analysis model. The proposed model needs to be expanded to include arterial as well without critical computation burden.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.185-192
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• 2011

More practical outputs and insights can be obtained through transportation analysis considering the time-dependent traffic movements. This study proposes a method of constructing time-dependent O-D trip tables for expressway corridor using real-world individual trip data. In this study, time-dependent O-D trip tables for the nationwide highway network are constructed based on toll collection system data. The proposed methodology is to convert nationwide time-dependent O-D trip tables into Korean expressway corridor O-D trip tables in order to deal with the computational complexity arising from simulating a large-scale traffic network. The experiment results suggest that actual individual trip record data can be used to effectively construct time-dependent O-D trip tables. They also imply that the construction of time-dependent O-D trip tables for the national highway networks along with those for Korean expressway developed in this study would make transportation analysis more practical and applicable to real-time traffic operation and control.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.195-215
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• 2011

The purpose of this article is to provide data to be utilized for marketing to attract future container cargo to the Korea-China Car Ferry Service and to estimate container traffic for the development of the International Passenger Terminal to be newly built in the Incheon Southern Port. An analysis of container traffic through the Passenger Terminal of Incheon Port showed that the container throughput of Incheon Port comprised 20% of traffic. The export cargo traffic in the International Passenger Terminal, 71.4%, or 111,698 TEU of 156,284 TEU in total, was brought from metropolitan areas. To increase the container traffic of the car ferry service currently concentrated on the metropolitan areas, more endeavor is required to strengthen marketing competence to attract container traffic to other regions apart from the metropolitan areas as well as provide general services.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.755-761
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• 2006

Though freight origin and destination data is essential for analysing transport investment and planning logistics facilities, the study on the establishment of the freight origin and destination data is very rare. The purpose of this study is to introduce a method on weight and expansion of sample freight data focusing on the Seoul metropolitan area. In particular, this study suggests the weight and expansion method which consider truck and commodity tonnage together. This paper also discuss the origin and destination trips in Seoul metropolitan area. This paper will contribute to establish more reliable freight origin and destination data.