• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.2
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• pp.133-141
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• 2021

The probe vehicle penetration rate is a required parameter in the estimation of entire volume, density, and queue length from probe vehicle data. The previous studies have proposed estimation methods without point detectors, which are based on probability structures for the locations of probe and non-probe vehicles; however, such methods are poorly suited to the case of multi-lane streets. Therefore, this study aimed to estimate the probe vehicle penetration rate at a multi-lane intersection and introduce a probability distribution of the queue length of each lane. Although a gap between estimates and observations was found, the estimates followed the trend of observations; the estimation could be improved by the correction factor hereafter. This study is expected to be used as a basic study for the estimation of entire volume, density, and queue length at multi-lane intersections without point detectors.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.123-133
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• 2008

Information collection systems and applications in a ubiquitous environment has emerged as a leading issue in transportation and logistics. A productive application example is a traffic information collection system based on probe vehicles and wireless communication technology. Estimation of hourly OD pairs using probe OD data is a possible target. Since probe OD data consists of sample OD pairs, which vary over time and space, computation of sample rates of OD pairs and expansion of sample OD pairs into static OD pairs is required. In this paper, the authors proposed a method to estimate sample OD data with probe data in Jeju City and expand those into static OD data. Mean absolute percentage difference (MAPD) error between observed traffic volume and assigned traffic volume was about 22.9%. After removing abnormal data, MAPD error improved to 17.6%. Development of static OD estimation methods using probe vehicle data in a real environment is considered the main contribution of this paper.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.262-274
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• 2019

The purpose of this study is to estimate the minimum proportion of probe vehicles for obtaining expressway traffic information using VISSIM, a micro traffic simulation model, between Yongin IC and Yangji IC on Yeongdong Expressway. 7,200 scenarios were created for the experiment, and 40 scenarios were adopted using the Latin hypercube sampling method because it was difficult to perform all the scenarios through experiments. The reliability of the experiment was improved by adding a situation when the general situation and the accident situation exist. In the experiments, the average travel time of probe vehicles at different market penetration rates were compared with the average travel time of the entire vehicles. As a result, the minimum market penetration rate of probe vehicles for obtaining expressway traffic information was found to be 45%. In addition, it is estimated that 25% market penetration rate of probe vehicle can meet 70% of traffic situations in accident scenario.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.17-32
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• 2022

This study explored an approach to estimate a flow-density diagram(FD) on a link in highway traffic environment by utilizing probe vehicles' time headway records. To study empirical flow-density diagram(EFD), the probe vehicles with vision sensors were recruited for collecting driving records for nine months and the vision sensor data pre-processing and GIS-based map matching were implemented. Then, we examined the new EFDs to evaluate validity with reference diagrams which is derived from loop detection traffic data. The probability distributions of time headway and distance headway as well as standard deviation of flow and density were utilized in examination. As a result, it turned out that the main factors for estimation errors are the limited number of probe vehicles and bias of flow status. We finally suggest a method to improve the accuracy of EFD model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.183-193
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• 2019

This study developed a shockwave detection and prediction of their extinction point method based on continuous wavelet transform using trajectory data from probe vehicles equipped with automotive sensors.. To analyze the effectiveness of the proposed method, this paper proposed two measures which are a distance error between the extinction points of the predictor and an time-location error of the extinction points. The proposed concept was proved using the micro simulation based experiment with three exogenous variables of traffic volume, lane-close duration, market penetration of probe vehicles. The analysis results show that the proposed method is capable of detecting the traffic shockwaves as well as predicting their extinction point, and also that the accuracy of the proposed method is highly dependent on the rate of the probe vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.33-40
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• 2010

In this paper, we consider three macroscopic traffic flow monitoring indices, Travel Time Index(TTI), Acceleration Noise(AN) and Two Fluid(TF) and investigate how to determine a proper rate of probe cars for producing reliable values of these indices. For the analysis, we use classical sampling theories and provide numbers of probe rates using simulation data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1851-1861
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• 2014

This study aims to calculate reliable sectional travel speeds with the consideration of the characteristics of the probe data collected in the interrupted traffic flow. First, in order to analysis the characteristics of the probe data, we looked into the distribution of the sectional travel times of each probe vehicle and compared the difference in the sectional travel speeds of each probe vehicle collected by DSRC. As a result, it is shown that outliers should be removed for the distribution of the sectional travel times. However, The comparison results show that the sectional travel speeds from the DSRC probe vehicles are not significantly different. Finally, based on the distribution characteristics of the sectional travel speeds of each probe vehicle and the representative values counted during a collection period, we drew the optimal outlier removal procedure and evaluated the estimation errors. The evaluation results showed that the DSRC sectional travel speeds were found to be similar to the observed values from actually running vehicles. On the contrary, in the case of the sectional travel speeds of intra-city bus, it was analyzed that they were less accurate than the DSRC sectional travel speeds. In the future, it will be necessary to improve BIS process and make use of the travel information on intra-city buses collected in real time to find various ways of applying it as traffic information.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.177-182
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• 2007

최근 텔레매틱스 분야에서 GPS 수신기를 장착한 probe car를 통해 교통 정보를 수집하는 방법에 대한 연구가 활발히 진행되고 있다. 이 방법은 기존에 교통 정보를 수집하기 위해 활용되고 있던 고정식 검지기들에 비해 수집되는 정보가 높은 신뢰성을 가지고, 도로 환경에 민감하지 않으며, 낮은 유지비용으로 운용할 수 있다는 장점을 가지고 있다. 하지만, probe car는 자신의 위치 정보를 교통 정보 센터로 전송해 주어야 하기 때문에 프라이버시가 노출될 수 있고, 주차되어 있는 시간에는 통행 정보를 보내줄 수가 없다. 이런 이유로 대중 교통차량이나 상업용 차량이 주로 probe car로 활용되어지게 되는데, 그 수가 많지 않을뿐더러 운행 구간이 고르게 분포되지 않아 probe car가 지나지 않는 구간, 즉 교통 정보 누락 구간이 존재할 수 있는 문제점을 가지고 있다. 본 논문에서는 교통 정보 누락 구간의 처리를 위해 과거의 이력 정보로 대체하는 방법, 주변 도로의 구간 정보로 예측하는 방법, 회귀 분석을 통한 예측 방법 등을 기술하고 실제 probe car들로 수집된 서울시 강남대로 구간의 자료로 각 방법에 대한 실험을 실시하여 각각의 방법에 대한 결과를 비교 분석한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.208-221
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• 2020

The objective of this study is to estimate and analyze the traffic density of continuous flow using the trajectory of individual vehicles and the headway of sample probe vehicles-front vehicles obtained from ADAS (Advanced Driver Assitance System) installed in sample probe vehicles. In the past, traffic density of continuous traffic flow was mainly estimated by processing data such as traffic volume, speed, and share collected from Vehicle Detection System, or by counting the number of vehicles directly using video information such as CCTV. This method showed the limitation of spatial limitations in estimating traffic density, and low reliability of estimation in the event of traffic congestion. To overcome the limitations of prior research, In this study, individual vehicle trajectory data and vehicle headway information collected from ADAS are used to detect the space on the road and to estimate the spatiotemporal traffic density using the Generalized Density formula. As a result, an analysis of the accuracy of the traffic density estimates according to the sampling rate of ADAS vehicles showed that the expected sampling rate of 30% was approximately 90% consistent with the actual traffic density. This study contribute to efficient traffic operation management by estimating reliable traffic density in road situations where ADAS and autonomous vehicles are mixed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.23-31
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• 2005

It is essential that is the collection of more accurate data to provide reliable traffic information. Currently collection of traffic information which uses the taxi or the passenger car by the probe vehicle is low reliability. If it develops the model which estimates car travel-time by using bus travel-time, it means that the sheep or duality of information using the passenger car and the taxi by the probe vehicle than will improve. Consequently the research which develops to each situation in accordance withtraffic volume and bus whole aspect car execution yes or no and bus stand form.