• 도로교통
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• s.99
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• pp.4-19
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• 2005

• Transportation Technology and Policy
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• v.2 no.3
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• pp.201-209
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• 2005

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.347-348
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• 2014

최근 급증하는 교통 혼잡으로 인해 시간적/물질적 손실이 크게 발생하고 있다. 이러한 교통난 해소는 시설투자만으로는 근본적인 해결책이 될 수 없다는 판단 하에 지난 수년간 보다 정확한 교통량을 예측하기 위해 시계열 기반의 다양한 교통량 예측 모델들이 개발 되어 왔다. 그러나 시계열 기반의 모델들은 회귀분석을 통해 과거 교통량을 분석하고 과거의 교통패턴이 미래에도 지속적으로 연장된다는 가정 하에 연구되었기 때문에 실시간으로 급변하는 불규칙한 교통 패턴에 대한 예측의 신뢰성을 떨어트린다. 또한 시계열 기반의 예측 기법은 어떠한 회귀분석 모델을 사용하는지에 따라 성능의 차이가 많이 나타나기 때문에 회귀분석 모델 선택이 중요하다. 이러한 제약을 극복하기 위해 본 논문에서는 은닉 마르코프 모델(Hidden Markov model)을 이용해 동적인 교통 패턴에 따라 현재 상황에 맞는 회귀분석 모델을 선택하는 신뢰도 높은 교통량 예측 시스템을 제안한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.1D
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• pp.71-80
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• 2012

Metropolitan transport demand has increased in Seoul Metropolitan Area (SMA) due to the expansion of its role and land use. Various public transport modes have to be supplied to relieve road congestions for the convenience of users. During the constructions of theses infrastructures some conflicts between the central government and local governments arise for sharing financial resources. In this study finance sharing criteria is developed for the metropolitan BRT, transfer facility, and public garages. Finally, a case study has been done for the metropolitan BRT between Cheongra and Hwagok area in SMA.

• Journal of the Korean Geographical Society
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• v.44 no.2
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• pp.187-205
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• 2009

Failures on network components of a public transportation system can give rise to the severe degradation of entire system functionality. This paper aims at exploring how potential failures can affect the system flows and reliability of subway network systems in Metropolitan Seoul. To evaluate the range of impacts of disruptions, this research employs a probabilistic approach, network reliability. Network reliability measures the network resiliency and probability of flow loss under a variety of simulated disruptions of critical network components, transfer stations in subway system. By identifying the best and worst scenarios associated with geographical impact, as well as evaluating the criticality of transfer stations, this research presents some insights for protecting current subways systems.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.395-396
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• 2014

최근 급증하는 교통 혼잡으로 인해 시간적/물리적 손실이 크게 발생하고 있다. 이러한 교통난 해소는 시설투자만으로는 근본적인 해결책이 될 수 없다는 판단 하에 지난 수년간 보다 정확한 교통량을 예측하기 위해 다양한 교통량 예측 모델들이 개발되어왔다. 그러나 기존 모델들은 회기분석을 통해 과거 교통량을 분석하고 과거의 교통패턴이 미래에 지속적으로 연장된다는 가정 하에 연구되었기 때문에 실시간으로 급변하는 불규칙한 교통 패턴에 대한 예측의 신뢰성을 떨어트린다. 이를 위해 본 논문에서는 큐잉 네트워크 모델 기반의 교통량 예측 모델을 설계 하고 이를 바탕으로 안드로이드 기반의 애플리케이션을 구현하였다.

• Journal of Korean Society of Transportation
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• v.16 no.4
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• pp.99-112
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• 1998

국가경제의 기반시설인 지역간 고속도로와는 달리 도시고속도로는 도시내 교통을 담당하는 교통시설로서 대부분의 도시에서 건설중이거나 운용 중에 있다. 연속류 도로라는 시설측면을 지역간 고속도로와 비슷하나 이용주체, 차량구성비, 정시성, 제한속도 등 그 성격에는 다소 차이가 있을 것으로 판단된다. 이런 이유에서 현재 도시고속도로의 계획이나 운영에 대한 지침이 지역간 고속도로의 계획 및 운영에 대한 지침과 동일시 되고 있다는 점은 불합리한 것으로 판단된다. 그러므로, 본 연구에서는 도시고속도로의 계획과 운영에 대한 지침을 마련하기 위해 현재 운영중인 대구신천대로를 대상으로 교통류특성 등 기초적 연구를 수행하였다. 연구결과를 간략하게 나타내면 다음과 같다. . 교통류 모형분석에서 기존의 Greenshield 모형이 설명력 90%이상을 나타냈다. . 승용차환산계수 분석에서 중형차량이 1.16, 대형차량이 1.47로 분석되었다. . 용량분석에서 최대관측교통량은 4,684pcphpl, 차두시간분석은 2,432pcphpl, 교통류 모형에서는 2,422pcphpl로 분석되어, 대구신천대로의 서비스용량은 2,300pcphpl에 가까운 것으로 판단되며, 차로폭, 측방여유폭에 따른 보정으로 이상적 조건에서의 용량은 약 2,400pcphpl로 분석되었다. 이 결과는 도시고속도로가 지역간 고속도로의 기본교통용량 2,200pcphpl보다 약 200대 정도 높을 것으로 추정된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.353-362
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• 2018

The national loss caused by the periodic livestock epidemic is very large. In addition, vehicle movement is the main cause of livestock epidemics in Korea. In this context, this study analyzed the relationship between the degree centrality of livestock facilities and the outbreak of infectious diseases. For this purpose, a livestock vehicle movement network was constructed using the facility entrance data provided by KAHIS. Afterwards, the centrality index was derived for each facility in the vehicle movement network and the mean centrality index of the epidemic and non-epidemic facilities were compared. The analysis results are summarized as follows. First, the degree centrality of epidemic facilities is significantly greater than non-epidemic facilities. As a result of the analysis of the entire period data and the period-based data, in most data, the degree centrality of facilities where livestock infectious diseases occurred was significantly greater than most non-occurrence facilities. Second, in the entire period data, the difference in degree centrality between the epidemic and non-epidemic facilities was smaller for HPAI than for FMD. On the other hand, no significant difference was found in the results of the analysis according to the divided period. The policy implications of the results are as follows. First, proactive management of facilities based on centrality is needed. Second, in the case of cloven-hoofed animal facilities, it is more urgent to introduce a management policy based on the degree centrality.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.195-209
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• 2024

The current road traffic signal controller developed in the 1990s has limitations in flexibility and scalability due to power supply problems, various communication methods, and hierarchical black box structures for various equipment and devices installed to improve traffic safety for road users and autonomous cooperative driving. In this paper, we designed a road traffic safety facilities equipment and devices integrated management system that can cope with the rapidly changing future traffic environment by solving the using direct current(DC) and power supply problem through the power over ethernet(PoE) technology and centralized data-driven control through message broker technology. In addition, a data-driven real-time control method for road traffic safety facilities equipment and devices operating based on time series data was implemented and verified.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.773-786
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• 2017

This study was to analyze data of climate change impacts on social infrastructure using text-mining methodology, and to visualize the spatial information by integrating those with regional data layers. First of all, the study identified that the following social infrastructure; power, oil and resource management, transport and urban, environment, and water supply infrastructures, were affected by five kinds of climate factors (heat wave, cold wave, heavy rain, heavy snow, strong wind). Climate change impacts on social infrastructure were then analyzed and visualized by regions. The analysis resulted that transport and urban infrastructures among all kinds of infrastructure were highly impacted by climate change, and the most severe factors of the climate impacts on social infrastructure were heavy rain and heavy snow. In addition, it found out that social infrastructure located in Seoul and Gangwon-do region were relatively largely affected by climate change. This study has significance that atypical data in media was used to analyze climate change impacts on social infrastructure and the results were translated into spatial information data to analyze and visualize the climate change impacts by regions.