• International Journal of Highway Engineering
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• v.13 no.2
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• pp.49-56
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• 2011

Understanding various casual factors affecting the occurrence of freeway traffic crash is a backbone of deriving effective countermeasures. The first step toward understanding such factors is to identify crash risks on freeways. Unlike existing studies, this study focused on the unsafe vehicle maneuvering that can be detected by in-vehicle sensors. The recent advancement of sensor technologies allows us to gather and analyze detailed microscopic events leading to crash occurrence such as the abrupt change in acceleration. This study used an accelerometer to capture the unsafe events. A set of candidate variables representing unsafe events were derived from analyzing acceleration data obtained by the accelerometer. Then, the crash risk was modeled by the binary logistic regression technique. The probabilistic outcome of crash risk can be provided by the proposed model. An application of the methodology assessing crash risk was presented, and further research items for the successful field implementation were also discussed.

• 한국ITS학회:학술대회논문집
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• 2005.11a
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• pp.19-24
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• 2005

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.1
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• pp.67-74
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• 2022

In recent, the number of real-time traffic information sources and providers has increased as increasing smartphone users and intelligent transportation system facilities installed at roadways including vehicle detection system (VDS), dedicated short-ranged communications (DSRC), and global positioning system (GPS) probe vehicle. The accuracy of such traffic information would vary with these heterogeneous information sources or spatiotemporal traffic conditions. Therefore, the purpose of this study is to propose an empirical strategy of heterogeneous information fusion to improve the accuracy of real-time traffic information. To carry out this purpose, travel speed data collection based on the floating car technique was conducted on 227 freeway links (or 892.2 km long) and 2,074 national highway links (or 937.0 km long). The average travel speed for 5 probe vehicles on a specific time period and a link was used as a ground truth measure to evaluate the accuracy of real-time heterogeneous traffic information for that time period and that link. From the statistical tests, it was found that the proposed fusion strategy improves the accuracy of real-time traffic information.

• 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.

• 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.26 no.2
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• pp.135-145
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• 2008

As a fundamental input to the travel demand forecasting, OD has been always a concern in obtaining the accurate link traffic volume. Numerous methods were applied thus far without a complete success. Some existing OD estimation techniques generally extract regular samples and expand those sample into population. These methods, however, leaves some to be desired in terms of accuracy. To complement such problems, research on estimating OD using additional information such as link traffic volume as well as sample link use rate have been accomplished. In this paper, a new approach for estimating static origin-destination (OD) using probe vehicle has been proposed. More specifically, this paper tried to search an effective sample rate which varies over time and space. In a sample test network study, the traffic volume error rate of each link was set as objective function in solving the problem. As a key result the MAE (mean absolute error) between expanded OD and actual OD was identified as about 5.28%. The developed methodology could be applied with similar cases. Some limitations and future research agenda have also been discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.14-27
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• 2009

Collection of invaluable real-time traffic data becomes available under ubiquitous transportation sensor networks (UTSN). Various research efforts have been made to utilize such useful data for deriving more accurate and reliable traffic information. This study presented a novel concept of decentralized traffic information and method to process traffic data which are obtained from inter-vehicle communications under the UTSN. In addition, an experimental evaluation to investigate the feasibility of the proposed method using probe vehicle data. Predictive travel times were estimated and evaluated for the feasibility investigation. Technical issues were derived and discussed to fully implement the proposed system. The outcomes of this study would be used as a guideline in designing better next-generation traffic information systems.

• Journal of the Korea Safety Management & Science
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• v.9 no.5
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• pp.97-101
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• 2007

As the use of vehicle route application and LBS(location based service) are fast grew, the importance of maintaining road network data is also increased. To maintain road data accuracy, we can collect road data by driving real roads with probe vehicle, or using digital image processing for the extraction of roads from aerial imagery. After compare the new road data to current database, we can update the road database, but that job is mostly time and money consuming or can be inaccurate. In this paper, an updating method of using GPS(global positioning system) enabled cell phone is proposed. By using GPS phone, we can update road database easily and sufficiently accurately.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.34-41
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• 2017

Vehicle to Infrastructure(V2I) communication means the technology between the vehicle and the roadside unit to provide the Intelligent Transportation Systems(ITS) and Telematic services. The vehicle collects information about the probe data through the evolved Node B(eNodeB) and after that eNodeB provides road conditions or traffic information to the vehicle. To provide these V2I communication services, we need a link adaptation technology that enables reliable and higher transmission rate. The receiver transmits the estimated Channel State Information(CSI) to transmitter, which uses this information to enable the link adaptation. However, due to the rapid channel variation caused by vehicle speed and the processing delay between the layers, the estimated CSI quickly becomes outdated. For this reason, channel interpolation and prediction scheme are needed to achieve link adaptation in V2I communication system. We propose the Advanced Discrete Prolate Spheroidal Sequence(ADPSS) channel interpolation and prediction scheme. The proposed scheme creates an orthonomal basis, and uses a correlation matrix to interpolate and predict channel. Also, smoothing is applied to frequency domain for noise removal. Simulation results show that the proposed scheme outperforms conventional schemes with the high speed and low speed vehicle in the freeway and urban environment.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.4
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• pp.84-91
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• 2010

Owing to revolutionary developments in automobile technologies, a variety of advanced vehicles - hybrid vehicle, hydrogen fuel-cell vehicle, electric vehicle, etc. - emerges recently. The safety is getting more important for developing automobiles. The electro-magnetic compatibility has to be assured, since those advanced vehicles are equipped with various new electronic systems. Electro-magnetic compatibility tests, in general, consist of an EMI(electro-magnetic interference) test and an EMS (electro-magnetic susceptibility) test. We investigated the susceptibility test method suggested in KMVSS (Korean Motor Vehicle Safety Standard) as the EMS test method. A series of experiments results that the above test method should be partially revised to comply with a Korean governmental standard method. In this paper, the some directions of modifications are presented to enhance the quality of the above EMS test method.