• Journal of Korean Society of Transportation
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• v.26 no.6
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• pp.123-132
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• 2008

Dynamic origin-destination (OD) trip matrix has been widely used for transportation fields such as dynamic traffic assignment, traffic operation and travel demand management, which needs precise OD trip matrix to be collected. This paper presents a quasi-dynamic OD matrix estimation model and applies it to real road network for collecting the dynamic OD matrix. The estimation model combined with dynamic traffic assignment program, DYNASMART-P, is based on GPS embedded in PDA, which developed for collecting sample dynamic OD matrix. The sample OD matrix should be expanded by the value of optimal sampling ratio calculated from minimization program. From application to real network of Jeju, we confirm that the model and its algorithm produce a reasonable solution.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.113-124
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• 2015

The KOTI(Korea Transport Institute) released the new version of KTDB(Korea Transport DataBase) in public. The new KTDB is different from the past KTDB in using the concept of trip generation and trip attraction instead of using the concept of Origin-Destination (OD), which was used in the past KTDB. Thus, the appropriate analysis method for future travel demand became necessary for the new type of KTDB. The method should be based on the concept of PA(Production-Attraction). This study focused on analysis of trip generation and trip distribution related to newly generated trips by future land developments. The study also described clearly the standardized forecasting process and methods with PA travel tables. The study showed that the analysis results with OD-based analysis can be different from the results with PA-based analysis in forecasting travel demand for a simple example case even though they used exactly same orignal travel data. Therefore, this study emphasized that a proper method should be applied with the new PA-based KTDB. It is necessary to prepare and disseminate guidelines of the proper forecasting method and application with PA-based travel data for practician.

• Journal of the Korean Society for Railway
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• v.19 no.5
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• pp.656-662
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• 2016

Based on time dependent location data of mobile phone users, users' ODs were produced after tracing their travel route and inducing their origins and destinations. System considered average signalizing frequency, which means that the longer the travel length is the more frequent the signal is. This is a home-based OD and is limited to the Seoul Metropolitan area. The OD matrix from the mobile phone data which was aggregated to the cell and transformed to the 'Dong' area, was compared to the KTDB OD. The results can be analyzed and it was determined that they are highly correlated because individual coefficients are 0.98 and 0.85, the former between the OD of this study and the KTDB Si/Gun/Gu unit area OD and the latter between the OD of this study and the Dong unit area KTDB OD.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.17-23
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• 2004

교통정책을 평가하기 위해 기본적으로 요구되는 Data 중 가장 근본이 되는 것이 OD이다. 기존의 교통정책을 평가함에 있어서 일반적으로 사용되고 있는 OD는 AADT(Annual Average Daily Traffic) OD이다. 계절별 평일/주말 교통량의 분산이 매우 크다는 것은 기존 조사나 연구로 익히 알려진 사실이며, 또한 사회 경제적인 여건의 변화 및 주 5일제 근무제의 시행 등으로 여가통행의 비중이 높아짐에 따라 평일과 주말의 교통량의 분산은 더욱 커질 것으로 예상된다. 따라서 교통정책을 평가하는 방법도 AADT OD의 일률적인 적용이 아닌 교통량의 계절별 평일/주말의 분산을 적용시킨 OD를 가지고 교통정책을 평가하는 방법이 교통정책을 결정함에 있어 오류를 범할 가능성을 적게 될 것으로 예상된다. 기존 연구에서는 이러한 교통량의 분산의 보정을 지점교통량에 한정하여 보정하고 있어 실질적인 네트워크 분석에 적용하기에는 무리가 있다. 이에 본 연구에서는 관측된 TCS Data를 이용하여 계절별 평일/주말의 OD 교통 패턴을 분석하여 계절별 평일/주말의 OD 교통패턴을 반영할 수 있는 보정계수를 산출하고 산출된 보정계수에 따라 AADT OD를 보정하여 네트워크 분석의 기초 자료를 구축하였다. 수정된 OD 교통량의 검증을 위하여 기존의 AADT OD의 인구당 통행발생비율과 계절별 평일/주말 OD의 통행발생량을 비교하였다. 그 결과 소수점 두 자리수에서 오차가 발생하여 비교적 합리적인 OD가 추정되었다. 또한 기존의 AADT OD를 이용하여 정책 결정을 할 때의 오류 가능성을 보이기 위하여 각 계절별 평일/주말 OD 교통량과 기존의 AADT OD를 입력 자료로 각각의 네트워크 분석 후 총통행시간의 차이를 분석하였다. 그 결과 정책 결정에 영향을 미칠 수 있을 정도의 차이가 있는 것으로 분석되었다.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.145-154
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• 2009

The main goal of this paper is to develop a methodology for increasing the reliability of truck OD matrices in Seoul Metropolitan Area. We propose a Hybrid Method made up of five processes by using Non-Traffic Assignment and Gradient Method. A Hybrid Method and Gradient Method have applied for comparison and estimation in Seoul Metropolitan Area. Mean Error and Root Mean Square Error of a Hybrid Method present lower than Gradient Method. The findings of this paper show that the new truck OD matrices created by a Hybrid Method are more reliable than the existing truck OD matrices in the Seoul Metropolitan Area.

• 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.31 no.3D
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• pp.355-361
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• 2011

In order to properly evaluate ITS services exposed in SMART Highway project, a confident dynamic origin-destination (OD) is inevitably needed. This paper used WAVE communication information as a part of call and response (C&R) communication which constitutes core part of the technology for constructing OD. This information includes node information and vehicle information (e.g., latitude and longitude) as well as trajectory data and sample path volume date calculated using node information and vehicle information. A procedure developed to construct a dynamic OD and to validate OD is consist of 1) making toy network and one-hour 00 (random distribution), 2) collecting link information and vehicle information, 3) constructing five-minute OD, and 4) validating estimated OD result using traffic volume and travel time simultaneously. The constructed OD is about 84.79% correct within less than 20% error range for 15min traffic volume, and about 85.42%, within less than 20% error rate of 15 min travel time. Some limitations and future research agenda have also been discussed.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.103-112
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• 2012

This research introduces a trip generation model reflecting time-series effects derived from a panel analysis with the data collected from the national household trip surveys conducted in 1996, 2002 and 2006. The existing methods are unable to reflect time-series effects from the change of socioeconomic conditions because the parameters applied to the model were basically from the base year of study - the parameter values were unchanged. This study proposes a new trip generation model developed through a panel analysis performed with the data collected from the last three national household trip surveys. From the results, it was found that the number of school trips increases and that the number of shopping trips decreases as time passes. The results showed that there are time-series effects affecting in trip generation.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.63-72
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• 2002

We applied 3-D balancing technique to estimate nationwide travel demand using travel behavior of Toll Collecting System data, socio-economic data in the region, and the data of several organizations connected with travel demand estimation. The results from this study were validated by the indices of RMSE(Root Mean Square Error), TLFD(Trip Length Frequency Distribution). TCS based inter-city average travel to measure of reliability and adequacy of estimated travel demand. Finally, 3-D technique seems to reflect more travel behavior of TCS OD than 2-D technique, but we cannot assert that 3-D technique superior to 2-D technique.

• Journal of Korean Society of Transportation
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• v.23 no.7 s.85
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• pp.125-136
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• 2005

The goal of this paper is to develop freeway Origin-Destination (OD) demand estimation model using VDS and AVI data. The formulation of methodology proposed in this paper includes traffic flow technique to be able to remove the bi-level problem and optimal solution algorithm using a kalman filter algorithm. The proposed dynamic OD estimation model use ilk and off-ramp volumes collected from VDS and partial OD collected from AVI data to raise the accuracy of dynamic OD estimation. The proposed model is evaluated by using the real-time data of SOHAEAN freeway, South Korea. The result of the proposed dynamic OD estimation model based on VDS and AVI data is better than that of based on VDS data. The more AVI systems are equipped at on and off-ramp, the more excellent result of estimation accuracy is expected.