• The Journal of Bigdata
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• v.7 no.2
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• pp.75-90
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• 2022

Recently, complex and sophisticated analysis of transportation is required due to changes in the socioeconomic environment and the development of bigdata technology. Especially, the revision of 3 laws including PERSONAL INFORMATION PROTECTION ACT makes it possible to combine various types of mobility data. But strengthen personal information protection makes inefficiency in utilizing mobility bigdata. In this paper, we proposed the "Virtual fusion methdology via mobility bigdata" which is a methodology for indirect data fusion for various mobility bigdata such as mobile data and transportation card data, in order to resolve legal restrictions and enable various transportation analysis. And we also analyzed regional bus passenger in Seoul capital area and Cheongju city with aforementioned methodology for verification. This methdology could analyze behavioral pattern of passenger with the MCGM(Mobility Comprehensive Genetic Map), graph with position and time, making with mobile data. Consquently, using MCGM, which is a result for indirect data fusion, makes it possible to analyze various transportation problems.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.135-142
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• 2006

The flow-density relations represent equilibrium relations between flow and density in the stationary state. Using individual vehicle data this paper proposed a method to 131ter traffic data in the stationary state and showed flow-density relations produced by the traffic data in the stationary state. The Proposed method is based on the idea that free flow and congested flow show totally different traffic behaviors and time series of the traffic data observed at detection stations. The traffic data collected from the stationary state in the free flow using this filtering method consist in the left branch of the flow-density relation and the traffic data collected from the stationary state in the congested flow consist in the right branch of the flow-density relation. The traffic data in the stationary state skew reproducible flow-density relation in the almost whole range of the traffic flow.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.89-95
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• 2008

In this paper, we propose an integrated techniques for managing data quality in traffic data warehousing environments. We describe how to collect and construct the traffic data warehouses from the operational databases, such as FTMS and ARTIS. We explain how to configure the traffic data warehouses efficiently. Also, we propose a quality management techniques to provide high quality traffic data for various analytical transactions. Proposed techniques can contribute in providing high quality traffic data to the traffic related users and researcher, thus reducing data preprocessing and evaluation cost.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.87-97
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• 2018

The traffic accident reports that are generated by the Traffic Broadcasting Networks(TBN) are unstructured data. It, however, has the value as some sort of real-time traffic information generated by the viewpoint of the drives and/or pedestrians that were on the roads, the time and spots, not the offender or the victim who caused the traffic accidents. However, the traffic accident reports, which are big data, were not applied to traffic accident analysis and traffic related research commonly. This study adopting text-mining technique was able to provide a clue for utilizing it for the impacts of traffic accidents. Seven years of traffic reports were grasped by this analysis. By analyzing the reports, it was possible to identify the road names, accident spot names, time, and to identify factors that have the greatest influence on other drivers due to traffic accidents. Authors plan to combine unstructured accident data with traffic reports for further study.

• Journal of Industrial Convergence
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• v.17 no.4
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• pp.53-58
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• 2019

It is important to collect and analyze the data from the traffic accident analysis system and the National Statistical Office to reduce the traffic accident rate of the elderly, who are the weakest. In particular, it is more important to analyze the data in areas where the elderly population is large and where accidents occur frequently. This paper visualizes and analyzes the data of elderly traffic accidents that occurred in recent 5 years in the area where many elderly people live in Buyeo-gun. The elderly traffic accident type, accident area, and location data of the elderly can be useful for the improvement measures and related decision making to reduce the elderly traffic accidents.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.125-126
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• 2014

센서 스트림 데이터는 센서 네트워크를 통해 수집되는 데이터로 실시간 처리를 요구하며, 연속적으로 끊임없이 발생하는 스트림 데이터이다. 이러한 스트림 데이터는 양이 방대하여 이를 저장하기가 매우 어려우며, 동시에 데이터를 검색하는 데에는 많은 시간이 소요된다. 본 논문에서는 센서 네트워크에서의 효율적인 스트림 데이터 처리 시스템을 제안한다. 이 시스템은 캐시테이블을 사용함으로써 데이터베이스에 최소화된 접근으로 데이터 스트림 관리 시스템의 성능을 개선하였다. 그리고 센서 네트워크에서 읽어 들여온 불완전 데이터를 효율적으로 정제하고 상위 단계로 전송한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.348-350
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• 2015

VTS 센터는 선박관제를 위해서 생성하는 실시간적인 해상교통정보를 생성하고 잇으며, 항만물류정보, 해양기상정보, 조선소 시운전 정보, 해상교통 환경정보, 선종별 운항정보, 사고 선박정보, 준사고 선박정보, 기타 정보 등을 수집하여 선박의 통항관제에 활용하고 있음에 따라 해상교통관제 시스템에 수집된 빅데이터의 처리방안에 대하여 고찰해 보았다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.24-25
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• 2019

최근 빅데이터 기술 개발로 방대한 데이터의 유의미한 분석 및 예측이 용이해졌다. 선박교통관제센터에서는 각종 센서와 다양한 정보를 기반으로 VHF 교신을 통해 선박교통관제를 수행한다. 관제사가 활용하는 레이더, AIS, Port-MIS. 센서 등의 데이터들이 디지털로 저장되고 있으며, 관제사의 VHF 교신내용은 디지털파일로 저장되어 선박교통관제센터의 서버 2개월간 보관된다. 본 논문에서는 관제 결과로 저장되고 있는 관제 로그 데이터를 활용하여 빅데이터를 구성하고 이를 기반으로 유의미한 정보를 생성할 수 있는 방안을 연구하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.110-116
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• 2021

W3C enacted RDF(Resource Description Framework based DCAT meta data standard, which is world-widely accepted so far. To guarantee the inter-operability and integrity of data from various sources and even from various countries, it is considered that transportation meta data should also follow the DCAT standard. But still, to represent the transportation domain-specific features, it is necessary to define new properties and vocabularies in addition to the DCAT standard. This research identified the additional properties and vocabularies for transportation metadata, considering uniqueness of transportation data. The revised RDF schema and RDF graph proposed in this research should be able to lead the transportation open data platform revitalization.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.117-118
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• 2014

최근 공공기관의 공공데이터 제공이 활성화 되고 있으며, 이를 활용한 응용서비스에 대한 요구도 증가하고 있는 추세이다. 현재 교통정보예측 플랫폼은 실시간 교통정보 또는 과거 교통정보이력을 분석하여 미래의 교통량이나 도착시간정보를 제공하고 있으나 날씨, 사고 등과 같은 미래 교통정보에 즉각적인 영향을 줄 수 있는 요소를 배제하고 있어 높은 신뢰도를 확보하기 어렵다. 본 논문에서는 교통정보예측에 영향을 주는 요소인 기상, 사고, 교통정보와 같은 공공데이터를 효율적으로 수집 저장 처리할 수 있는 저장방식 및 신뢰도 높은 교통정보를 예측할 수 있는 예측기술이 포함된 b-Traffic 서비스 플랫폼을 제시한다.