• 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 the Korean Regional Science Association
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• v.31 no.1
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• pp.21-42
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• 2015

This paper investigates whether urban expansion and the vitalization of the local economy can be achieved through new city development. The results show that regardless of the starting point (origin) or destination point, traffic increases closer to the origin for the purpose of transportation and decreases farther from the origin. However, traffic tends to increase in districts 20 to 40 km away from the origin. Hence, building a new city in this district may be effective in terms of geography and functionality.

• Journal of Korean Society of Transportation
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• v.28 no.5
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• pp.131-139
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• 2010

The transport mode choice problem is to determine which of the alternative transport modes connecting an origin and destination will be used by a traveler. Most of the research relating to transport mode choice have mainly been focused on modeling, properties, and applications of the model, but rarely were concerned with equilibrium among the modes. This paper proves the equilibrium among the modes by using a logit mode choice model, and then verifies it with the Korean Transport Database (KTDB). In order to obtain such an equilibrium, this paper also presents a solution algorithm based on the fixed point theorem. The algorithm was tested with an example and confirmed the equilibrium solution.

• 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.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.05a
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• pp.9-14
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• 2005

교통정책과 계획수립에 가장 중요한 의사결정 과정은 통행수요 분석이고, 이에 활용되고 있는 필수적인 기초 데이터베이스는 분석용 네트워크와 기종점 통행량이 있다. 통행수요 추정과정의 합리성이 보장되도록 하기 위해서는 이러한 기본 입력 자료의 신뢰성은 중요하다. 하지만, 일반적으로 분석용 네트워크를 구축할 때 예산과 분석기간의 제약 때문에 실세계의 교통망 중 많은 부분을 단순화 시켜서 구축한다. 또한 기 구축된 네트워크에 대해서도 변경되는 교통망을 반영하기 위해 네트워크를 수정, 편집할 때에도 많은 재원과 시간이 소요된다. 본 연구에서는 이러한 문제점을 보완하고자 교통분석 목적의 패키지(EMME/2, TranPlan) 혹은 범용의 GIS 패키지(ArcGIS)에서 직접 이용할 수 있도록 기 구축된 네트워크를 기반으로 GIS 데이터로의 변환 혹은 네트워크를 추출하는 양방향 데이터 교환 시스템을 개발하였다. 이러한 GIS-T 통합 시스템은 네트워크의 편집과 분석에 효율적인 환경을 제공하여 보다 현실적인 교통망 모델링을 반영할 것으로 기대되며 다양한 교통문제에 대한 분석에 효과적인 도구로 활용될 수 있을 것이다.

• Journal of Korean Society of Transportation
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• v.4 no.1
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• pp.41-71
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• 1986

본 연구는 $\ulcorner$네트웍$\lrcorner$ 평형모형을 이용하여 일반비용극수(Generalized Cost function)의 모형계수를 결정하는 하나의 방법을 제시한다. 이러한 기법은 동일모형을 실현 하기 위해서는 필연적인 과정이다. 기존의 대부분의 방법은 도시통행상 발생되는 통행자의 제비용을 직접 관측하고 수집하여 모형체계를 결정하였지만 본 연구에서는 이미 활용가능한 기종점별 통행실태조사를 이용하여 통행비용을 내생적으로 결정하고 이에 따른 모형체계를 추출한다. 따라서 본 연구는 자료수집상에 야기될 수 있는 제반 문제점의 행결과 동일목적 의 산출과정을 단순화시키고 내적일관성을 추구하였다는 데에 의의가 있다. 연구의 타당성 검토를 위해 $\ulcorner$시카고$\lrcorner$ 지역에 본 모형과 방법론을 적용하고 결과를 분석하였다.

• 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.27 no.6
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• pp.167-176
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• 2009

Several travel demand management schemes have been used for controlling overloaded traffics on urban area. To maximize efficiency of the travel management, traffic manager has to set target level that we try to arrive in advance, and then to find optimal variable to attain this goal. In this regard, this paper presents two travel demand management models, expressed by mathematical program, and also presents their solution algorithms. The first is to find optimal travel demand for origin-destination (OD) pair, based on average travel time between the OD pair, and the second is based on the ratio of volume over capacity on congested area. An example is given to test the models.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.3
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• pp.343-357
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• 2012

The Seoul metropolitan subway system can be represented by a graph which consists of nodes and edges. In this paper, we study classification of subway stations and trip behaviour of subway passengers through partitioning the graph of the subway system into roughly equal groups. A weight of each edge of the graph is set to the number of passengers who pass the edge, where the number of passengers is extracted from the transportation card transaction database. Since the graph partitioning problem is NP-complete, we propose a heuristic algorithm to partition the subway graph. The heuristic algorithm uses one of two alternative objective functions, one of which is to minimize the sum of weights of edges connecting nodes in different groups and the other is to maximize the ratio of passengers who get on the subway train at one subway station and get off at another subway station in the same group to the total subway passengers. In the experimental results, we illustrate the subway stations and edges in each group by color on a map and analyze the trip behaviour of subway passengers by the group origin-destination matrix.

• 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.