• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.588-594
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• 2016

As more populations are getting older, the number of vulnerable pedestrians is increasing, thereby social problems related to transportations also frequently occur in different areas and situations. Many of such problems come from bus drivers who may pass bus stops not recognizing passengers about to board. In this paper, we propose a new IoT bus notification system developed to avoid these situations. Our implementation aims to gain bus service routes using publicly opened data, notify passengers about bus stop locations using GPS information and finally deliver the positions of those passengers to the bus drivers so that they can hardly miss passengers who are willing to board on the right stop. By creating an application, it was conducted by means of a GPS to communicate the location of the vehicle by means of GPS and transfer data to the location of the vehicle. Experimental results show that it is possible to accurately determine the position of passengers even in a crowded race area. The average error distance is 31m, and if the data to be processed as error is excluded, it provides a high reliability as 19m.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.600-607
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• 2009

In order to obtain continuous navigation information at low cost, we demonstrate, in this work, a position system which is constructed by integrating accelerometers with GPS. The proposed system eliminates vibration and noise elements of accelerometers by using Kalman filter. Calculating continuous navigation information is executed by unifying GPS position data and accelerations of moving and centripetal directions which affect the vehicle. Through simulations and experiments, we show that the performance of GPS can be improved by employing accelerometers. Our proposed system can provide stable and seamless position information where the GPS signal is unavailable due to obstruction like tunnels, and high buildings. The designed system can be implemented at low cost of circuit design and production, and satisfy various installation conditions.

• Journal of Biosystems Engineering
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• v.43 no.3
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• pp.247-254
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• 2018

Purpose: Although previous studies have performed on-farm evaluations for the control of airborne diseases such as foot-and-mouth disease (FMD) and influenza, disease control during the process of livestock and manure transportation has not been investigated thoroughly. The objective of this study is to predict common patterns of livestock-vehicle movement. Methods: Global positioning system (GPS) data collected during 2012 and 2013 from livestock vehicles on Jeju Island, South Korea, were analyzed. The GPS data included the coordinates of moving vehicles according to the time and date as well as the locations of livestock farms and manure-keeping sites. Data from 2012 were added to Esri software ArcGIS 10.1 and two approaches were adopted for predicting common vehicle-movement patterns, i.e., point-density and Euclidean-distance tools. To compare the predicted patterns with actual patterns for 2013, the same analysis was performed on the actual data. Results: When the manure-keeping sites and livestock farms were the same in both years, the common patterns of 2012 and 2013 were similar; however, differences arose in the patterns when these sites were changed. By using the point-density tool and Euclidean-distance tool, the average similarity between the predicted and actual common patterns for the three vehicles was 80% and 72%, respectively. Conclusions: From this analysis, we can determine common patterns of livestock vehicles using previous year's data. In the future, to obtain more accurate results and to devise a model for predicting patterns of vehicle movement, more dependent and independent variables will be considered.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2003.04a
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• pp.145-150
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• 2003

Mobile mapping system is a surveying system that use vehicle carrying various sensors as CCD camera, GPS and IMU(Inertial measurement Unit). This system capturing images of forward direction continuously while running road. Use these images, then acquire road and road facilities information as facilities position, size or maintenance condition. In this study, we organized data and each data processing steps that are needed for 3 dimensional positioning. And develop digital photogrammetry S/W easy to use and accurate for mobile mapping system.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.47-56
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• 2009

Effective detection and correction of outliers of raw traffic data collected from the field is of keen interest because reliable traffic information is highly dependent on the quality of raw data. Global positioning system (GPS) based traffic surveillance systems are capable of producing individual vehicle speeds that are invaluable for various traffic management and information strategies. This study proposed a locally weighted regression (LWR) based filtering method for individual vehicle speed data. An important feature of this study was to propose a technique to generate synthetic outliers for more systematic evaluation of the proposed method. It was identified by performance evaluations that the proposed LWR-based method outperformed an exponential smoothing. The proposed method is expected to be effectively utilized for filtering out raw individual vehicle speed data.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.17-27
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• 2006

Car following model is a theory that examines changes of condition and interrelationship of acceleration deceleration. headway, velocity and so on closely based on the hypothesis that the Posterior vehicle always follows the preceding vehicle. Car following mode) which is one of the research fields of microscopic traffic flow was first introduced in 1950s and was in active progress in 1960s. However, due to the limitation of data gathering the research depression was prominent for quite a while and then soon was able to tune back on track with development in global positioning system using satellite and generalization of computer use. Recently, there has been many research studies using reception materials of global Positioning system(GPS). Introducing GPS technology to traffic has made real time tracking of a vehicle position possible. Position information is sequential in terms of time and simultaneous measurement of several vehicles in continuous driving is also practicable. Above research was focused on judging whether it is feasible to overcome the following model research by adopting the GPS reception device that was restrictively proceeded due to the limitation of data gathering. For practical judgment, we measured the accuracy and confidence level of the GPS reception devices material by carrying out a practical experiment. Car following model is also being applied in simulations of traffic flow analysis, but due to the difficulty of estimating parameters the basis of the above result. it is our goal to produce an accurate calibration of car following model's parameters that is suitable in this domestic actuality.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.173-184
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• 2018

As the portable traffic information collection system using probe vehicles spreads, it is becoming possible to collect road hazard information such as portholes, falling objects, and road surface freezing using in-vehicle sensors in addition to existing traffic information. In this study, we developed a integration and decision algorithm that integrates time and space in real time when multiple probe vehicles detect events such as road hazard information based on GPS coordinates. The core function of the algorithm is to determine whether the road hazard information generated at a specific point is the same point from the result of detecting multiple GPS probes with different GPS coordinates, Generating the data, (3) continuously determining whether the generated event data is valid, and (4) ending the event when the road hazard situation ends. For this purpose, the road risk information collected by the probe vehicle was processed in real time to achieve the conditional probability, and the validity of the event was verified by continuously updating the road risk information collected by the probe vehicle. It is considered that the developed hybrid processing algorithm can be applied to probe-based traffic information collection and event information processing such as C-ITS and autonomous driving car in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.48-56
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• 2009

Regulation of Visible Light Transmission Percentage (VLT%) has been argued because it was known that the degree of darkness of tinted vehicle can affect to driving maneuver. Previously, it was proven that low level of VLT affects capacity reduction. But, due to lack of field data they could not analyze the effect of Car-Following model parameters. This study focuses on the effect of a tinted vehicle on following traffic flow. RTK GPS receiving data through field experiment analyzed based on headway distance, acceleration noise, sensitivity, and reaction time. As a result of analysis through GM 1st Model and 3rd Model, influence of following vehicle vary inversely with VLT and risk according as tinting of lead vehicle is third vehicle bigger than second vehicle. Also the results patterns of GM 3rd model include distance-headway are same with GM 1st Model. In the further need to research for influence analysis of traffic flow stability by the level of VLT.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.67-74
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• 2019

In this paper, we design and implement an analytics platform based on bulk cargo DTG data for crackdown on overloaded trucks. DTG(digital tachograph) is a device that stores the driving record in real time; that is, it is a device that records the vehicle driving related data such as GPS, speed, RPM, braking, and moving distance of the vehicle in one second unit. The fast processing of DTG data is essential for finding vehicle driving patterns and analytics. In particular, a big data analytics platform is required for preprocessing and converting large amounts of DTG data. In this paper, we implement a big data analytics framework based on cargo DTG data using Spark, which is an open source-based big data framework for crackdown on overloaded trucks. As the result of implementation, our proposed platform converts real large cargo DTG data sets into GIS data, and these are visualized by a map. It also recommends crackdown points.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.10
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• pp.1017-1025
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• 2008

The air data system(ADS) was developed for unmanned aerial vehicle(UAV) in this paper. Generally, the ADS helps flight control computer(FCC) to control the UAV above the stall speed and to hold the given altitude. The accurate measurement of airspeed and altitude of UAV is important because it indicates a flight performance and assures a safe flight. The ADS consists of MEMS pressure sensors, a lowpass filter, a micro controller unit and a pitot-tube. The ADS errors were reduced by pressure and temperature compensation of MEMS sensors. Finally, the altitude and airspeed data of the ADS was compared with GPS data in the flight test.