• 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.

• 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.

• 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.

• Journal of Korean Society of Transportation
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• v.10 no.1
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• pp.55-62
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• 1992

교통수요는 교통정책 및 교통시설 계획의 수립 및 평가에 중요한 영향을 미치게 되므로 교통수요의 예측은 교통연구에서 중요한 부문을 차지하고 있다. 도로밑에 설치된 전자차량감지기(Electronic Vehicle Detector)로부터 자동 수집된 링크 교통량 자료(Traffic Counts)를 주요 입력자료로 이용하여 계획지역의 기종점 통행표(Origin Destination Trip Matrix)를 작성할 수 있는 기법 들이 최근 수년동안 많이 발달하게 되었다. 이러한 새로운 기법들은 가구조사(Home Inteview), 노변면접조사(Road-Side Interview)등을 토하여 조사된 자료를 기초로하는 전통적은 4단계 교통수요추정방법(Conventional 4-Stage Estimation Method)-통행발생(Generation), 통행분포(Distribution), 수단선택(Modal Split), 교통배분(Assignment)-과 비교하여 첫째로 정확도가 높은 링크 교통량 자료를 별도의 조사를 거치지 않고서도 수집이 가능하기 때문에 조사비용이 거의 들지 않아도 되어 경제적이고, 둘째로 전통적인 수요예측방법들에서 요구되어지는 복잡한 모형수립 및 계수조정(Parameter Calibration)이 필요하지 않아 간편하고 셋째로 오래전에 작성된 기종점 통행표를 단순히 링크 교통량 자료만을 이용하여 쉽게 보완할 수 있어 지속적인 자료의 축적(Data Age-ing)이 가능하며 더 나아 가서 소위 연속적인 교통 계획 및 교통시설관리(Continuous Transport Planning and Management)를 가능케 하는 등의 여러 장점 때문에 많은 주목을 받아 오고 최근 몇 년이 꾸준히 실무에 유용하게 적용이 되고 있는 실정이다. 본 연구는 링크 교통량자료를 이용하여 기종점 통행표를 작성하기 위하여 개발된 기존의 여러 기법들 가운데 특히 용량제약조건(Capacity-Restrained Condition)하에서 기존의 방법들을 상호 검토한 후 Wardrop의 교통망 평형원칙(Wardrop's First Network Equilibrium Principle)을 만족하는 새로운 추정기법을 제의하고 이의 시험결과를 논의하는 것을 주요내용으로 한다. 링크 교통량 자료를 이용하여 기종점 통행표를 작성하는 기법들의 근본 목표는 조사된 링크 교통량(Ob-served Traffic Counts)에 가장 근접한 교통망 통행 배정 링크 교통량(Assigned Link Volumes)을 재현(Re-producing)할 수 있는 기종점 통행표들 중에서 최적의 기종점 통행표를 발견하는 것이다. 따라서 교통망에서 통행자의 여행 경로 배정을 가장 잘 반영할 수 있는 현실적인(Realistic) 교통망 통행 배정 모형(Net-work Traffic Assignment Model)의 선택은 중요한 요소가 되며 특히 교통망에 교통체증(Traffic Conges-tion)이 심할 경우 교통망 통행자 평형조건(Network Traffic Equilibrium Condition)을 고려하기 위한 특별한 처리가 요구되어진다. 본 연구는 Whllumsen(Hall, Van Vliet and Willumsen, 1980)에 의하여 개발된 ME2(Maximum Entropy Matrix Estimation)기법에서 반복식 추정방법(Sequential Estimation Method)을 사용할 경우 Wardrop의 평형조건을 만족하는 기종점 통행표를 구할 수 없다는 단점을 극복하기 위한 방안으로서 엔트로피 극대화문제와 교통망 평형 조건(Entropy Maximisation and Network Equilibrium Condition)의 두 문제를 동시에 해결할 수 있는 새로운 수식모형과 이를 풀기 위한 알고리즘(Simultaneous Solution Algorithm)을 제의하였다. 제의된 수식모형과 알고리즘을 예제 교통망(Example Network)을 이용한 시험하고 그 결과를 ME2 의 반복식 추정 방법으로부터 구한 기종점 통행표와 비교 검토하였다.

• 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.

• 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.

• 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.

• 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.

• 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 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.