• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.41-41
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• 1998

ITS틀 내의 한 분야인 도로교통정보체계 (ATIS: Advanced Traveler Information system)는 실시간 교통정보를 운전자에게 직접 제공하는 것으로서, 이를 위해 매 순간마다 가로망에 배정되는 교통량 및 통행시간을 예측할 수 있는 범용의 동적 통행배정모형(dynamic route choice model)의 개발이 필히 수반되어야 한다. 본 연구에서는 ITS사업에서 필수적으로 수반되어야 할 최적 제어이론에 의한 동적 통행 배정모형을 ATIS의 핵심 소프트웨어로 응용하기 위해 기존 연구성과를 발판으로, 순간 동적 통행 배정모형(Ran, Boyce &LeBlanc, 1993)의 통행제약조건인 링크통행함수, 특히, 과부하 시 엘켈릭의 일반식의 파라메터를 조정, 적용하여, 서울시 강남지역의 실제 가로망의 사례연구를 통해 지체식의 각각의 파라메터에 따른 결과를 O/D에 따른 통행시간, 링크통행시간, 혼잡도를 중심으로 비교 평가하여, ATIS의 핵심 소프트웨어로서 순간 동적 통행배정을 통해 보다 현실여건을 잘 반영할 수 있는 링크 통행 성능 함수를 도출하였다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.255-256
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• 2023

본 연구에서는 코로나19로 인하여 전국적으로 전례 없는 통행체계 위축 등 통행행태 변화가 발생되어 수도권 및 인천시 지역적 세부 통행체계에 대하여 네트워크 중심성 분석을 통하여 지역별 교통 거점과 외부 영향에 따른 지역적 교통 거점 변화를 비교 분석하였다. 또한, 대중교통 이용통행 분석 결과, 코로나19 유행 시기별로 통행량이 크게 감소됨에 따라 버스, 지하철 등 수단별 대책 마련하는데 기여할 것으로 판단된다.

• Journal of Korean Society of Transportation
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• v.31 no.2
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• pp.45-59
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• 2013

This study deals with the comparative analysis between two freight demand estimation methods : Unimodal O/D based method and P/C based method. The data of access/egress truck trips has been omitted from the Korean freight unimodal O/D of KTDB. This is because KTDB's unimodal O/D has not marked the series of unlinked trips down as the whole freight intermodal transport and surveyed only the main-haul trips of them. For these reasons, freight intermodal transport mechanism has not been analysed perfectly with Korean unimodal O/D data. This study tries to estimate P/C table of Korean Import/Export container freight and develop the MCC(Multimodal Channel Choice) model. Then, comparing unimodal O/D based method and P/C based method in terms of the switch commodities between production point(the initial point of freight transport) and consumption point(the terminal point of freight transport), unimodal commodities, and commodities on links is conducted. The results show that the P/C based method is able to simulate the freight intermodal transport.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.102-115
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• 2016

In this study, a scheme of ramp metering that uses Off-ramp Exit Percentage instead of the O/D table required for systems of integrated control of ramps at the target freeway segment is presented. The segment from Gyeyang IC to Jangsu IC on the Seoul Outer Ring Expressway was selected for the study because the segment frequently shows large volume of traffic on the short distance between the two ICs requiring an integrated on-ramp control by taking the traffic situation on an entire expressway into account despite an unavailability of O/D data. Thus the information of Off-ramp Exit Percentage at each IC were collected instead of securing the O/D table through actual survey, and the congestion on the segment was analyzed to identify the validity of the use of off-ramp traffic instead of O/D data. In addition, the scheme of ramp metering that exploits the off-ramp traffic information was prepared through simulations conducted in a way supporting the traffic control for respective access roads thereof by taking traffic situations and queues on each ramp into account. The results obtained from the simulation analyses revealed an improved level of travel speed and traffic volume on the main line and validated the use of off-ramp traffic instead of the O/D table for the ramp metering.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.705-713
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• 2024

Purpose: Currently, the only routes that enter Yeongjong Island are Yeongjong Bridge and Incheon Bridge, which are private roads. The purpose of this study is to predict and study changes in transportation demand for new routes and two existing routes according to the plan to open the 3rd Bridge, a new route, in December 2025. Method: The basic data for traffic demand forecast were O/D and NETWORK data from 2021.08, KOTI. In order to examine the reliable impact of Yeongjong Bridge and Incheon Bridge on the opening of the 3rd Bridge, it is necessary to correct the traffic distribution of Yeongjong Island and Incheon International Airport to suit reality, and in this study, the trip distribution by region was corrected and applied using Mobile Big Data. Result: As of 2026, the scheduled year of the opening of the 3rd Bridge, two alternatives, Alternative 1 (2,000 won) and Alternative 2 (4,000 won), were established and future transportation demand analysis was conducted, In the case of Alternative 1, which is similar to the existing private road toll restructuring, the traffic volume of the 3rd Bridge was predicted to be 42,836 out of 199,101 veh/day in the Yeongjong area in 2026, and the traffic volume reduction rate of the existing road was analyzed as 21.5%. Conlclusion: As a result of the review (based on Alternative 1), the proportion of convertted traffic on the 3rd Yanji Bridge was estimated to be 70% of Yeongjong Bridge and 30% of Incheon Bridge, and 21.5% of the predicted traffic reduction on the existing road when the 3rd Yanji Bridge was opened is considered appropriate considering the results of the case review and changes in conditions. It is judged that it is a way to secure the reliability of the prediction of traffic demand because communication big data is used to reflect more realistic traffic distribution when predicting future traffic demand.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.155-168
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• 2018

In this study, we studied the directional pattern of entering the intersection from the intersection upstream link prior to predicting short future (such as 5 or 10 minutes) intersection direction traffic volume on the interrupted flow, and examined the possibility of traffic volume prediction using traffic assignment model. The analysis method of this study is to investigate the similarity of patterns by performing cluster analysis with the ratio of traffic volume by intersection direction divided by 2 hours using taxi DTG (Digital Tachograph) data (1 week). Also, for linking with the result of the traffic assignment model, this study compares the impact area of 5 minutes or 10 minutes from the center of the intersection with the analysis result of taxi DTG data. To do this, we have developed an algorithm to set the impact area of intersection, using the taxi DTG data and traffic assignment model. As a result of the analysis, the intersection entry pattern of the taxi is grouped into 12, and the Cubic Clustering Criterion indicating the confidence level of clustering is 6.92. As a result of correlation analysis with the impact area of the traffic assignment model, the correlation coefficient for the impact area of 5 minutes was analyzed as 0.86, and significant results were obtained. However, it was analyzed that the correlation coefficient is slightly lowered to 0.69 in the impact area of 10 minutes from the center of the intersection, but this was due to insufficient accuracy of O/D (Origin/Destination) travel and network data. In future, if accuracy of traffic network and accuracy of O/D traffic by time are improved, it is expected that it will be able to utilize traffic volume data calculated from traffic assignment model when controlling traffic signals at intersections.

• 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.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.127-132
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• 2012

In the Seoul metropolitan bus network, it may be necessary for a bus passenger to pick up a parcel, which has been purchased through e-commerce, at his or her convenient bus stop on the way to home or office. The flow-capturing location-allocation model can be applied to select pickup points for such bus stops so that they maximize the captured passenger flows, where each passenger flow represents an origin-destination (O-D) pair of a passenger trip. In this paper, we propose a fast heuristic algorithm to select pickup points using a large O-D matrix, which has been extracted from five million transportation card transactions. The experimental results demonstrate the bus stops chosen as pickup points in terms of passenger flow and capture ratio, and illustrate the spatial distribution of the top 20 pickup points on a map.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.605-612
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• 2019

Traditionally, travel demand forecasts have been conducted based on the data collected by a survey of individual travel behavior, and their limitations such as the accuracy of travel demand forecasts have been also raised. In recent, advancements in information and communication technologies are enabling new datasets in travel demand forecasting research. Such datasets include data from global positioning system (GPS) devices, data from mobile phone signalling, and data from call detail record (CDR), and they are used for reducing the errors in travel demand forecasts. Based on these background, the objective of this study is to assess the feasibility of CDR as a base data for travel demand forecasts. To perform this objective, CDR data collected for Daegu Metropolitan area for four days in April including weekdays and weekend days, 2017, were used. Based on these data, we analyzed the correlation between CDR and travel demand by travel survey data. The result showed that there exists the correlation and the correlation tends to be higher in discretionary trips such as non-home based business, non-home based shopping, and non-home based other trips.