• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.31-41
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• 2006

The main purpose of this paper is to develop the practical method to estimate the congestion price in odor to overcome the difficulty of traditional microeconomics approach for demand and cost function concepts. In this paper, we estimate the theoretical congestion toll which reflecting the real traffic conditions such as a speed-density functions using a traffic engineering methods We calculates the optimal congestion toll based on the real traffic conditions assuming that the electronic road pricing (ERP) systems ave installed for the study road. After evaluating the various speed-density relationship methods. we found that the Drake model is best suited for the Gangbyeon Expressway Using the Drake model, the optimal congestion toll will be 94 to 3,255 Won for the traffic speed between 44km/h to 68 km/h based on wage rate method and 107 to 6,381 Won for the marginal substitution method for the Gangbyeon Expressway in city of Seoul, Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.49-58
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• 2006

The purpose of this study is to develop transportation-sensitive land use densities in a metropolitan context. It analyses traffic impacts according to 20 different development density scenarios in the downtown Seoul, and estimates the density ceiling. The results identify that the transportation-wise sustainable density in the downtown can be extended up to the FAR level of 460% with an option of 2,000 won congestion charge levied on the downtown area. It also finds that the region-wide sustainability measured by congestion level can be improving as the level of congestion charge increases. Without the congestion charge, however, the density ceiling slides down to 430%. It is recommended that, in order to bring in higher density developments in the region, transportation demand management (TDM) measures are indispensible.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.99-111
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• 2018

Service areas in expressways are very important facilities in terms of efficient expressway operation and the convenience of users. It needs a traffic management strategy to inform drivers in advance about congestion in service areas so as to distribute users of service areas. But due to the lack of sensors and data on numbers of people in the service areas, congestion in service areas had not been measured and managed appropriately. In this study, a congestion index for service areas was developed using telecommunication floating population big data. Two alternative indices (i.e., density of service areas and floating population V/c of service areas) were developed. Finally, the floating population V/c of service areas was selected as a congestion index for service areas for reasons of the ease of understanding and comparison.

• Journal of Korean Society of Transportation
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• v.22 no.3 s.74
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• pp.159-166
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• 2004

The capacity concept presented in the Highway Capacity Manual is for steady-state traffic flow assuming that there is no restriction in downstream flowing, which is traditionally used for planning, design, and operational analyses. In the congested traffic condition, the control objective should be to keep the congested regime from growing and to recover the normal traffic condition as soon as possible. In this control case, it is important to predict the spatial-temporal pattern of congestion evolution or dissipation and to estimate the throughput reduction according to the spatial-temporal pattern. In this context, the new concept of dynamic capacity for managing congested traffic is developed in terms of spatial-temporal evolution of downstream traffic congestion and in view of the 'input' concept assuming that flow is restricted by downstream condition rather than the 'output' concept assuming that there is no restriction in downstream flowing (e.g. the mean queue discharge flow rate). This new capacity is defined as the Maximum Sustainable Throughput that is determined based on the spatial-temporal evolution pattern of downstream congestion. And the spatial-temporal evolution pattern is estimated using the Newell's simplified q-k model.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.179-191
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• 1999

To device effective freeway traffic flow control strategies and freeway traffic information dissemination strategies, it is very important to estimate real physical queue length on the freeway. Shock wave theory and queueing theory have limitation to be used to estimate the queue length. The primary objective of this study is to develop a reliable method for estimating the physical queue length and level of congestion. Queueing propagation processes were analysed by using such traffic data as main line traffic volume, ramp volume, density. speed, and physical queue length collected by video photographing on Olympic Freeway. As a result of analysis, it has been confirmed that the real queue length can be estimated by using the traffic counts arriving the congested region and passing a bottleneck location. Further more, a reliable method for estimating the level of congestion could be developed on the basis of real-time traffic counts.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.574-576
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• 2005

유무선 통합망 환경에서 TCP는 무선망에서의 통신오류 밀 핸드오프를 혼잡으로 인한 패킷 손실로 간주하여 혼잡제어 메카니즘을 동작시키기 때문에 네트워크의 전반적인 효율을 저하시킨다. 이러한 문제점을 해결하기 위한 방안으로 무선망에서의 TCP 성능을 개선하기 위한 연구가 다양하게 진행되어 오고 있다. 그 중에서 Snoop 프로토콜은 종단간의 의미 구조를 유지하면서 무선망의 패킷 손실을 지역 재전송을 통하여 최소화하는 방식으로 통신오류에는 좋은 성능을 보여주지만, 대량의 무선 데이터 유입시 buffer overflow가 발생할 가능성이 높다. 따라서 본 논문에서는 버퍼관리 기법을 이용하여 buffer overflow 상황을 미연에 방지하여 불필요한 혼잡제어 메카니즘을 호출하는 것을 방지하면서 네트워크의 전반적인 효율을 향상시키는 방안을 제안하였다.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.2
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• pp.107-118
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• 2018

Due to the rapid economic development, traffic congestion has become a dire concern in Beijing, China. Levying a congestion toll is seen as the most effective solution to the problem. Building a congestion pricing model is a crucial step in implementing a workable toll scheme. Unlike previous attempts, this study not only covers the theoretical discussion but also considers three practical issues: the speed-density relationship, the value of travel time savings, and the determination of optimal traffic volume. We estimate the speed-density relationship by regression models and the value of travel time saved through survey results. We further suggest a way through which the government could identify the optimal traffic flow by a series of trial-and-errors, without the knowledge of exact road demand structure. Finally, a practical tolling scheme is proposed for Beijing's second ring road along with some policy recommendations.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.4
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• pp.613-624
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• 2015

This study examined: 1) the effect of store density on perceived crowding 2) the difference of perceived price benefit of sale by store density 3) the effect of perceived price benefit and store density on perceived crowding and 4) the effect of perceived crowding and price benefit on shopping behaviors. Store density and perceived crowding were categorized into social and spatial dimensions. Data were collected with 6 (high, medium, and low social and spatial densities) * 2 (sale and no-sale) between-subjects experimental designs. A total of 395 responses were analyzed. The results revealed that social density affected social crowding, but spatial density had no effect on perceived crowding. Price benefit of sale was not different by store density. The sale itself did not affect perceived crowding. Under the social density situation, perceived price benefit reduced spatial crowding and social crowding showed a positive effect on purchase behavior while spatial crowding had a negative effect. However, the most important effect on purchase behavior was price benefit. The study implies that social density (not spatial density) is important for consumer behavior and retail strategies.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.275-277
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• 2018

선박 및 해상교통관제에 있어서 교통 혼잡구역에 대한 선박교통밀도 예측은 선박충돌사고 예방에 중요하다. 선박 교통밀도 예측정보는 사전에 진입하는 선박들에게 속력조정, 우회항로 이용 등 사전 조치가 가능하다. 본 연구에서는 해상 선박교통상황을 딥러닝 네트워크에 학습한 주의구역 선박교통류 예측 모델(Ship Traffic Extraction Network, STENet)을 제안하여 주의구역의 선박교통류 예측을 수행하고자 한다. STENet 모델 학습을 위해 여수해역 AIS 데이터를 전처리하고, 생성된 입력(해상교통상황)-출력(주의구역 교통밀도) 쌍 데이터를 적용하여 STENet 모델을 학습하였다. 학습된 모델을 이용하여 선박교통류 예측을 한 결과, 중기예측은 표준 절대 오차(mean absolute error)가 0.4-0.5척이 였으며, 장기예측은 0.7-0.8척의 오차로 기존의 Dead Reckoning에 의한 방법보다 50% 이상 교통밀도 예측성능이 향상 되었다.