• 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.

• Journal of Korean Society of Transportation
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• v.19 no.5
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• pp.49-59
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• 2001

In the transportation planning process, origin and destination(O-D) trip matrix is one of the most important elements. There have been developments and applications of the methodology to adjust old matrices using link traffic counts. Commonly, the accuracy of an adjusted O-D matrix depends very much on the reliability of the input data such as the numbers and locations of traffic counting points in the road network. In the real application of the methodology, decisions on the numbers and locations of traffic counting points are one of the difficult problems, because usually as networks become bigger, the numbers of traffic counting points are required more. Therefore, this paper investigates these issues as an experiment using a nationwide network in Korea. We have compared and contrasted the set of link flows assigned by the old and the adjusted O-D matrices with the set of observed link flows. It has been analyzed by increasing the number of the traffic counting points on the experimental road network. As a result of these analyses, we can see an optimal set of the number of counting links through statistical analysis, which are approximately ten percentages of the total link numbers. In addition, the results show that the discrepancies between the old and the adjusted matrices in terms of the trip length frequency distributions and the assigned and the counted link flows are minimized using the optimal set of the counted links.

• Journal of the Korean Society for Railway
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• v.11 no.4
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• pp.417-423
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• 2008

Transportation planners are increasingly adopting policies aimed at changing travel choices made by general commuter. Theories on the relationship between high-speed technology and transport address changes in travel behavior of regional commuter due to alterations in the Kyung-Bu railroad transportation corridor. The purpose of this paper is to examine the relationships between travel behavior and high-speed technology. The KORAIL data allows us to explore the differences between travel characteristics that are usually hard to discern by guesswork. The effects of travel time were found to be significant in the full decisions that control for commuting KTX. Although many argue that transportation behavior cannot be changed, this paper demonstrates that about 4 years of behavioral data on KTX travel show otherwise. In this paper we explore several possibilities to fill in some of the gaps in our knowledge on the expansion of commuter belt.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.53-63
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• 2003

The Origin-Destination(OD) matrix is very important in describing transport movements in a region. The OD matrix can be estimated using traffic counts on links in the transport network and other available information. This information on the travel is often contained in a target OD matrix and traffic counts in links. To estimate an OD matrix from traffic counts, they are the major input data which obviously affects the accuracy of the OD matrix estimated, Generally, the quality of an estimated OD matrix depends much on the reliability of the input data, and the number and locations of traffic counting points in the network. Any Process regarding the traffic counts such as the amount and their location has to be carefully studied. The objective of this study is to select of the optimal location of traffic counting points for the OD matrix estimation. The model was tested in nationwide network. The network consists of 224 zones, 3,125 nodes and 6,725 links except to inner city road links. The OD matrix applied for selection of traffic counting points was estimated to 3-constrained entropy maximizing model. The results of this study follow that : the selected alternative to the best optimal counting points of six alternatives is the alternative using common links of OD matrix and vehicle-km and traffic density(13.0% of 6,725 links), however the worst alternative is alternative of all available traffic counting points(44.9% of 6,725 links) in the network. Finally, it should be concluded that the accuracy of reproduced OD matrix using traffic counts related much to the number of traffic counting points and locations.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.171-182
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• 2001

Travel Time is an important characteristic of traffic conditions in a road network. Currently, there are so many road users to get a unsatisfactory traffic information that is provided by existing collection systems such as, Detector, Probe car, CCTV and Anecdotal Report. This paper presents the results achieved with Data Fusion Model, Hybrid Neuro Fuzzy System for on - line estimation of travel times using RTMS(Remote Traffic Microwave Sensor) and Probe Data in the signalized arterial road. Data Fusion is the most important process to compose the various of data which can present real value for traffic situation and is also the one of the major process part in the TIC(Traffic Information Center) for analyzing and processing data. On-line travel time estimation methods(FALEM) on the basis of detector data has been evaluated by real value under KangNam Test Area.

• Journal of Korean Society of Transportation
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• v.19 no.2
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• pp.53-60
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• 2001

본 논문의 목적은 대중교통 노선배정 시에 여러 수단간의 환승을 고려함으로써 다수단 대중교통망 내에서 수단선택과 노선선택을 동시에 수행할 수 있도록 확률적인 통행배분(traffic assignment) 모형의 하나인 다이알 알고리즘을 응용할 것을 제시하고 그 알고리즘의 속성을 정확하게 규명하는데 있다 승용차의 확률적 통행배분모형으로 잘 알려져 있는 Dial 알고리즘은 로짓모형에 기초한 것이므로 다수단간의 대중교통 수단선택과 노선선택과 같은 선택 행태를 동시에 설명할 수 있는 모형적 특성을 기본적으로 내재하고 있다. 본 연구에서 제시한 대중교통 노선선택에 적용될 수 있도록 수정된 다이알 알고리즘은 기존의 결정적 대중교 통 노선배정 모형들의 단점을 극복할 수 있는 특성을 갖고 있다. 즉 결정적 대중교통 노선배정모형은 기종점간 최단경로에 교통량을 전랑배분(All-or-Nothing)하여 통행자들의 행태적 속성을 제대로 반영하지 못하고 있으며, 다수단 대중교통망 내에서 환승을 포함한 복합 대중교통수단의 선택을 효용극대화 이론에 기초하지 않고 최소비용노선에 전량배분하는 모형의 한계점을 갖고 있다. 이러한 결정적 대중교통 노선배정모형의 단점을 수정된 다이알 알고리즘은 개선할 수가 있다. 본 연구에서는 알고리즘의 특성을 파악하기 위한 모의실험으로 Sioux Falls 형태의 대중교통 네트워크를 이용하여 기존의 알고리즘과 비교 분석하였다. 분석의 탄력성을 갖고 있는 수정된 대중교통 다이알 알고리즘이 현실적 대중교통 통행패턴을 기존 모형보다 합리적으로 설명할 수 있을 것으로 보이며, 특히 다수단 대중교통망이 형성된 대도시의 대중교통 정책분석에 적합한 기법이 될 수 있을 것으로 고려된다.

• Journal of Korean Society of Transportation
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• v.33 no.6
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• pp.575-583
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• 2015

The Korea Transport Institute (KOTI) builds the origin and destination(O-D) trip data with relatively smaller zone size such as Eup, Myeon, Dong administration unit districts in metropolitan area. Otherwise, O-D trip data was built by bigger size of traffic analysis zone(TAZ) such as Si, Gun, Gu administration unit districts for rural area. In some cases, it is needed to divide a zone into several sub-zones for rural area in order to analyze travel distribution pattern in detail for a certain highway and rail project. The study suggested a method to estimate O-D trips for sub-zones in the larger-size zones in rural area. Two different distribution models, direct demand model and gravity model, were calibrated for sub-zone's intra-zonal O-D trip pattern with metropolitan area O-D data which has smaller zone-size (sub-zone) data categorized by low, middle and high population density. The calibration results were compared between the two models. The gravity model with impedance function of power functional form was selected with better explanation for all groups in the metropolitan area. The adjusted $R^2$ was 0.7426, 0.6456 and 0.7194 for low, middle and high population density group, respectively. The suggested O-D trip estimating method is expected to produce enhanced trip patterns with sub-divided small zones.

• Journal of Korean Society of Transportation
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• v.19 no.3
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• pp.115-131
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• 2001

The Purpose of this study is to develop a simulation model for large-scale network with interrupted flow as well as uninterrupted flow. The Cell Transmission(CT) theory is used to simulate traffic flow. Flow transition rules have been newly developed to simulate traffic flows at merging and diverging sections, and signalized intersections. In the model, it is assumed that dynamic OD table is exogenously given. Simulation results for toy network shows that the model can explain queue dynamics not only in signalized intersections of urban arterials, but also in merging and diverging sections of freeway. In case study, the model successfully simulated traffic flows of 145,000 vehicles on CBD network of city of Seoul with 74 traffic zones, 133 signalized intersections among 395 nodes and 1110 links.

• The Journal of Bigdata
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• v.5 no.2
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• pp.85-95
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• 2020

In this study, a mobility analysis method is suggested to estimate an O/D trip demand estimation using Mobile Phone Signaling Data. Using mobile data based on mobile base station location information, a trip chain database was established for each person and daily traffic patterns were analyzed. In addition, a new algorithm was developed to determine the traffic characteristics of their mobilities. To correct the ping pong handover problem of communication data itself, the methodology was developed and the criteria for stay time was set to distinguish pass by between stay within the influence area. The big-data based method is applied to analyze the mobility pattern in inter-regional trip and intra-regional trip in both of an urban area and a rural city. When comparing it with the results with traditional methods, it seems that the new methodology has a possibility to be applied to the national survey projects in the future.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.83-97
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• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.