• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.110-123
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• 2019

Traffic data is the most basic element necessary for transportation planning and traffic system operation. Recently, a method of estimating traffic flow characteristics using distance to a leading vehicle measured by an ADAS camera has been attempted. This study investigated the feasibility of the ADAS vehicle reflecting the distance error of image-based vehicle identification technology as a means to estimate the traffic flow through the normalized root mean square error (NRMSE) based on the number of lanes, traffic demand, penetration rate of probe vehicle, and time-space estimation area by employing the microscopic simulation model, VISSIM. As a result, the estimate of low density traffic flow (i.e., LOS A, LOS B) is unreliable due to the limitation of the maximum identification distance of ADAS camera. Although the reliability of the estimates can be improved if multiple lanes, high traffic demands, and high penetration rates are implemented, artificially raising the penetration rates is unrealistic. Their reliability can be improved by extending the time dimension of the estimation area as well, but the most influential one is the driving behavior of the ADAS vehicle. In conclusion, although it is not possible to accurately estimate the traffic flow with the ADAS camera, its applicability will be expanded by improving its performance and functions.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.39-50
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• 2006

This study aims to introduce a basic principle to improve the incident detection algorithm using traffic flow diagrams that can classify traffic states with a high reliability on the basis of the analysis of traffic flow characteristics under the recurrent or incident congestions. It is tried to newly classify the traffic states with the speed-flow and speed-occupancy diagrams. This is because McMaster algorithm has a tendancy on not identifying the traffic states exactly using the flow-occupancy diagram. In this study it shows that the classification of traffic states is applicable to use speed-occupancy relationship Therefore, it is necessary to determine some parameters to correctly classify the areas representing the traffic states and it may be possible to develop a new algorithm to detect the incident with a high reliability.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.67-79
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• 2002

In this paper, observed trajectories of a vehicle platoon are viewed as one realization of a finite sequence of random trajectories. In this point of view, we develop novel and mathematically rigorous concept of traffic flow variables such as local traffic density, instantaneous traffic flow, and velocity field and investigate their nature on a general probability space of a sequence of random trajectories which represent vehicle trajectories. We present a simple model of random trajectories as an illustrative example and, derive the values of traffic flow variables based on the new definitions in this model. In particular, we construct the model for the sequence of random vehicle trajectories with a system of stochastic differential equations. Each equation of the system nay represent microscopic random maneuvering behavior of each vehicle with properly designed drift coefficient functions and diffusion coefficient functions. The system of stochastic differential equations nay generate a well-defined probability space of a sequence of random vehicle trajectories. We derive the partial differential equation for the expected cumulative plot with appropriate initial conditions. By solving the equation with numerical methods, we obtain the values of expected cumulative plot, local traffic density, and instantaneous traffic flow. In addition, we derive the partial differential equation for the expected travel time to a certain location with appropriate initial and/or boundary conditions, which is solvable numerically. We apply this model to a case of single vehicle trajectory.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.144-152
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• 2018

This study focuses on collecting traffic data using drones to compensate for limitation of the data collected by the existing traffic data collection devices. Feasibility analysis was performed to verify the traffic data extracted from drone videos and optimal methodology for extracting data was established through analysis of various data reduction scenarios. It was found from this study that drones are very economical traffic data collection devices and have strength of determining the level-of-service(LOS) for uninterrupted flow condition in a very simple and intuitive way.

• 한국디지털정책학회:학술대회논문집
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• 2004.05a
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• pp.593-608
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• 2004

우리나라의 경우 교통정보수집용 검지기는 루프검지기가 주종을 있으며, 지금까지 한국에서 루프검지기를 대체할 수 있는 영상 및 초단파검지기와 같은 대체검지기에 대한 평가는 단속류 보디는 연속류 상황에 대한 평가로 제한되어 왔다. 한편 최근들어 점차 고속도로를 중심으로 영상검지기의 설치개소수가 급속히 증가하고 있는 추세이다. 이 영상검지기의 경우 연속 교통류 상황의 15 분 혹은 5 분 단위의 점유율, 교통량, 속도등의 교통변수 측정정확도는 검지시스템의 요구사항을 충족하는 것으로 나타났다. 본 연구에서는 한국의 장래 교통관리 첨단화에 요구되는 교통자료 수집수준을 시가지도로 및 고속도로를 중심으로 파악하고, 루프검지기의 대체 검지기로서 영상검지기에 대한 성능평가 및 분석을 실시하였다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.60-66
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• 2009

The acceleration noise is valuable index to monitor traffic stability. However, the previous study was performed for the acceleration noise of individual vehicle. The consideration of the acceleration noise for vehicle in the network has not been studied yet. This paper proposes a new macroscopic traffic flow monitoring method based on applying network acceleration noise.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.115-126
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• 2009

The lane-change behavior usually consists of discretionary lane-change and mandatory lane-change types. For the first type, drivers change lanes selectively to maintain their own driving condition and the second type is the case that the drivers must change the current lane, which can occur in recurrent congestion sections like merging and weaving sections. The mandatory lane-change behavior have a great effect on the operation condition of freeway. In this paper, we first generate data such as traffic volumes, speeds, densities, and the number of lane-change within the merging and weaving sections using the data of individual vehicle collected from time-lapse aerial photography. And then, the data is divided into the stable and congested flow by analyzing the speed variation pattern of individual vehicles. In addition, the number of lane-changing from ramp to mainline within every 30-meter interval is investigated before and after traffic congestion at study sites and the distribution of lane-changing at each 30-meter point is analyzed to identify the variation of lane-changing ratio depending on the stable and congested flows. To recognize the effect of mainline flow influenced by ramp flow, this study also analyzes the characteristics of the lane-changing distributions within the lanes of mainline. The purpose of this paper is to present the basic theory to be used in developing a lane-changing model at the merging and weaving sections on freeways.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.45-60
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• 1997

본연구의 목적은 1994년과 1995년의 연구 결과를 토대로 고속국도 교통류의 차량 추종, 차선 변경 특성을 현장 조사 자료를 통하여 분석·규명하고, 국내 고속도로의 교통류 특성을 반영할 수 있는 한국형 고속국도 모의실험 모형을 개발하는데 있다. 본 연구의 주요 결과는 다음과 같다. ▶ 국내 고속국도 교통류의 차두시간, 속도, 차량군의 크기, 차선 변 경, 중차량의 영향 등의 특성을 조사·분석하여 관련 매개변수와 모형식을 도출하였다. ▶ 차량 생성 모형은 개별 차량의 차두시간, 속도를 이용하여 구축하였으며, 중차량의 구성 비 율에 따른 속도 변화를 연구하여 그 결과를 모형 구축에 응용하였다. ▶ 차량 추종 모형은 1995년 연구에서 검증된 PITT-KLD 모형에 기반을 두었으며, 현장 실측 자료를 분석하여 차량 추종과 관련된 매개변수들을 설정하였다. ▶ 차선 변경 모형은 기본적으로 간격 수락 모형을 이용하였으며, 차선 변경시 임계 간격을 국내 운전자들의 유형에 따라 10가지로 설 정하였다. 차선 변경 확률은 현장 조사 자료를 기초로 한 경험적 모형을 구축하여 선정하였 으며, 마코프 연쇄 기법과도 비교·검토하였다. ▶ 개발된 모의실험 모형을 비교·평가하기 위 해 고속국도 합류부의 현장 조사 자료와 모의실험 모형을 비교·평가한 결과, 합류 이전 단 계에서는 실측치와 모형의 통계량이 어느 정도 유사한 양상을 보이지만 합류 이후 단계에서 는 차이를 나타내고 잇다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.116-126
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• 2013

Weather factor to affect driver's driving environment are due to changes in weather conditions is caused rainfall, snowfall, fog etc and the reducing of road capacity and because deteriorating weather could be affect the headway and vehicle speed and the decrease in lane caused by an accident occurs that was analyzed that bad weather occur congestion greater than on the clear day. Bad weather to reduce of the driver's visibility was analysed the sensitive to changes in travel speed and traffic accident to appears high characteristics according to weather conditions on the expressway(higher speed) than general road. As a result, visibility have been determined to be important factor in changes of the highway traffic flow characteristics. Therefore, in this study, we selected traffic volume and travle speed that have a major impact on high-speed expressway basic segments as importance effect factor and we selected to subject of analysis among the Metropolitan Expressway that it could be obtained certain level of traffic volume data and we studied the changing of expressway traffic flow due to change visibility after the collecting of meteorological and traffic data. In order to perform this study, data collection and analysis methods were established through the existing literature and we had selected level of visibility of the expressway and we had performed the statistical verification. Finally, we had calculated the rate of change of expressway traffic flow characteristics due to visibility and we had come up with a way to apply at capacity and service level analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2D
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• pp.105-111
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• 2010

Operating speed is one of key elements in the design and operation of freeway. Few studies have been carried out macroscopically to find characteristics of free-flow speed (FFS) using small sample size and not considering the conditions of traffic volume and the effects of hour periods. As an attempt to find out the characteristics of FFS, this study microscopically analysed both the distributions of freeway FFS and percentile speeds according to traffic volume and daily hour periods using huge sample size. It was found out that speed distributions are changed and showed different behaviors under the conditions of traffic volumes(1-5 veh/30sec) and daily hour periods(0-5, 6-8, 9-11, 12-19, 20-23). V85(85th percentile speed) at morning, night, and midnight period decreases according to increase in traffic volume respectively, whereas V85 at day time does not show considerable differences. So the behaviors of V85 according to hour periods dramatically changed according to the increase in traffic volume.