• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.77-87
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• 2018

Traffic Density is the most important of the three primary macroscopic traffic stream parameters, because it is most directly related to traffic demand(Traffic Engineering, 2004). It is defined as the number of existing vehicles within a given distance at a certain time. However, due to weather, road conditions, and cost issues, collecting density directly on the field is difficult. This makes studies of density less actively than those of traffic volume or velocity. For these reasons, there is insufficient attempts on divers collecting methods or researches on the accuracy of measured values. In this paper, we used the 'Density Measuring System' based on the synthesise technology of several camera images as a method to measure density. The collected density value by the 'Density Mesuring System' is selected as the true value based on the density define, and this value was compared with the density calculated by the traditional measurement methods. As a result of the comparison, the density value using the fundamental equation method is the closest to the true value as RMSE shows 1.8 to 2.5. In addition, we investigated some issues that can be overlooked easily such as the collecting interval to be considered on collecting density directly by calculating the moment density and the average density. Despite the actual traffic situation of the experiment site is LOS B, it is difficult to judge the real traffic situation because the moment density values per second are observed max 16.0 (veh/km) to min 2.0 (veh/km). However, the average density measured for 15 minutes at 30-second intervals was 8.3-7.9 (veh/km) and it indicates precisely LOS B.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.177-185
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• 2002

본 논문의 목적은 링크통행시간 자료를 수집하는 시스템에서 소요 프로브차량대수에 영향을 주는 요소들을 규명하고. 최적의 소요 프로브차량대수를 결정하는 모형을 개발하는데 있다. 자가용승용차, 택시, 버스, 택배차량 등 여러 종류의 차량들이 프로브차량으로 사용될 수 있다. 그러나 일정한 정확도 이상의 교통정보를 수집하기 위해서 얼마나 많은 프로브차량이 필요한지에 대한 연구는 그다지 깊이 있게 이루어지지 않았다. 적정 소요 프로브차량대수는 링크통행시간 자료수집 기술 수집대상 링크의 공간적 범위, 프로브차량의 종류 및 운행 특성, 자료수집 시스템의 신뢰도, 수집되는 자료의 정확도 등에 영향을 받게 된다. 소요 프로브차량대수를 결정하는 링크당 평균 통행시간 자료수, 프로브차량 밀도의 최소 확률, 그리고 자료 미수집링크의 허용비율의 3가지 결정기준이 정의되었다. 또한 이러한 결정기준에 대해 소요 프로브차량대수를 산출하는 모형이 개발되었다. 일반적으로 주기당, 링크당 평균 필요 통행시간 자료수$(d_R)$, 단위길이당 프로브차량의 대수 또는 밀도$(n_{min} or {\alpha})$, 일정 프로브차량밀도 이상의 확률($\beta$), 그리고 자료 미수집링크의 비율($\gamma$)이 클수록 소요 프로브차량대수는 증가한다. 민간 교통정보회사의 통행시간 수집시스템에서 소요 프로브차량대수를 산정하는 사례연구가 수행되었으며, 여러가지 조건에서 소요 프로브차량대수가 산출되었다.

• Journal of Korean Society of Transportation
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• v.23 no.8 s.86
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• pp.53-66
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• 2005

This paper analyzes the effects of acceleration lane lengths on the traffic characteristics of merging areas. Two merging areas, Suwon IC and Singal JC, which have remarkably different acceleration lane length were selected as field study sites. Traffic data were collected through dividing each merging area into several subsections. Not only conventional flow, speed and density data but also a newly introduced MOE, density variation were used to analyzed the characteristics of merging area. Singal JC which has longer acceleration lane than Suwon IC showed more severe congestion, and the cause of the results was figured out.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.779-784
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• 2011

Freeway FFS (Free-Flow Speed) under the state of LOS (Level of Service) A has been regarded as a homogeneous state to all levels of traffic volume. The features of low-density FFS is served as the basic data for a decision on limited maximal speed, accident analysis, simulation modeling etc. A few researches for the macroscopic characteristics of design and operation speed have been reported, and any study for the microscopic features of freeway free-flow speed under the state of low density has not been done. Therefore, the characteristics of low-density FFS according to the level of traffic volume (1-3 veh/30 sec) and daily hour periods (0-5, 6-8, 9-11, 12-19, 20-23) is microscopically analyzed in this study with huge volume and speed data. It was found that speed distributions are changed and show different behaviors under the conditions of traffic volume levels and daily time periods. V85s (85th percentile speed) at early morning and night periods decrease when levels of traffic volume increase, whereas V85s at day time do not show considerable differences. Especially, FFSs of levels of traffic volume at early morning and night periods, despite low density, is analyzed as heterogeneity, but homogeneity at day time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2575-2580
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• 2013

In this paper, we watch out key measure of the level of transportation service about travel time and delay time. And we measured vehicle traffic by moving vehicle method using CCTV which is one of the travel time measure. We should be measured in place of continuous traffic flow characteristics with wide traffic light interval. In addition, traffic flow on the other side of the interval must be sufficiently identifiable and at the end of this section must be possible U-turn. This method it requires only the driver of the vehicle because of the CCTV measure. In addition, We cannot require time, distance, and traffic equipment that can be recorded. Because equipped with the software to do that. In addition to traffic, average travel time, average space speed, traffic density are also available.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.244-257
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• 2017

Traffic congestion occurs from drivers' human factors such as driver reaction time, reckless lane change, and inexperienced driving. When Automated Vehicles are introduced, human factors are excluded, resulting in increased average vehicle speed, stabilizing traffic flow, and increasing road capacity. This study analyzed traffic flow changes through traffic volume-speed-density plots, and increased road capacity due to Automated Vehicles. As a result of the analysis, when rate of automated vehicles gests higher, the traffic flow became stable. Additionally, it was analyzed that when all vehicles were automated, the road capacity increased by about 120 %. It is expected that there will be a positive expectation in terms of traffic congestion and traffic demand management due to the introduction of Automated Vehicles.

• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.535-541
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• 2013

Expressways are built to provide for high levels of safety and efficiency in the movement of large traffic volumes at high speeds. However, Gyeongbu and Namhae expressways in the country which are often suffering from the transportation problems with increased import and exoprt cargo trucks including the container vehicles are the major expressways having the Busan Port as the origin and destination regions, and are required to study the expressway traffic characteristics for reducing the transportation problems. We therefore attempted to suggest the expressway density predictive model through the correlation analysis between lane occupancy and mean density at the 8-lane basic segments of the above major expressways in the country.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.84-84
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• 2019

본 연구에서는 홍수터 식생 밀도 변화에 의한 하안침식 관계를 정량적으로 분석하고, 사주의 거동과 사행하천의 발달 관계를 실내실험을 통하여 정량적으로 분석하였다. 이를 정량적으로 파악하기 위하여 수치모형을 적용하여 그 특성을 분석하였다. 시간이 증가함에 따라, 사주의 이동속도는 감소하였다. 하폭이 증가하면서 수심과 소류력이 감소하고, 사행도가 감소하였기 때문이다. 식생의 밀도가 증감함에 따라, 사주의 이동속도가 감소하였다. 식생의 밀도가 증가함에 따라 하안침 식량은 감소하였다. 식생의 밀도가 상대적으로 낮은 곳에서는 저수로가 일정한 형상을 유지하면서 횡방향과 하류로 이동하였다. 시간이 증가함에 따라 저수로의 사행도가 증가하고 있으나, 식생의 밀도가 상대적으로 높은 하도에서는 저수로 사행도가 거의 변화가 없다. 식생밀도가 낮은 곳에서 무차원 곡률반경이 가장 크고, 하안침식속도가 가장 빠르다. 식생밀도가 가장 높은 곳에서는 무차원 곡률반경이 가장 작고, 하안침식속도가 가장 낮았다. 하도 식생은 저수로를 분할시켜서 새로운 저수로가 형성된다. 식생하천에서 하천의 이동, 분할, 저수로 사행도를 변화시키는데 중요한 역할을 한다. 또한 식생의 영향을 고려하여 자유사행의 발달과정을 수치모의 결과, 사행의 발달과정을 잘 모의하였으며, 식생의 밀도가 높은 곳에서 사주의 이동속도는 빠른 특성을 보여주었다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.59-66
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• 2006

This study was to construct the linear density predictive models on the on-ramp junctions in urban freeway. From the analyses of the real-time traffic characteristic data, and the construction and verification of the linear density predictive models, the models showed a considerable explanatory power with the determination coefficients ($R^2$) of over 0.7 between the density and speed data. Also, they showed a considerably high correlativeness with the correlation coefficients (r) of over 0.8 between the calculated density data and the expected ones estimated by the models.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.605-608
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• 2010

본 논문에서는 가공되지 않은 축적된 교통 정보를 이용하여 교통 전문가와 교통공학 분야의 학생들이 손쉽게 교통 정보를 분석할 수 있는 통합 교통 정보 분석 시스템을 제안한다. 제안하는 시스템은 도시 고속도로 내의 구간과 시간, 일자를 선택하고, 선택한 영역의 교통 수집 정보를 분석하여, 교통 흐름 제어나 교통 정보 분석에 필요한 다양한 정보와 함께 속도 및 밀도, 통행량을 이용한 등고선 그래프를 제공한다.