• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.602-612
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• 1997

With GPS carrier phase measurements from more than two antenna which attached to the vehicle, precise attitude can be easily obtained if the integer ambiguity included in carrier phase measurement is resolved. Recently some special products which use dual frequencies or has one receiver engine with multiple antenna are announced. But there are still strong requirements for the conventional single frequency off-the-shelf receiver. To meet these requirements, an efficient integer ambiguity resolution technique is indispensable. In this paper, a new technique to resolve integer imbiguity with single frequency receivers is proposed. The proposed method utilize the known baseline length as a constraint of independent elements of integer ambiguities. With this constraints, the size of search volume can be greatly reduced. Thus the true integer ambiguity can be easily determined with less computational burden and number of measurements. The proposed method is applied to real data to show its effectiveness.

• IE interfaces
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• v.23 no.4
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• pp.349-356
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• 2010

The role of Intelligent Transportation System (ITS) is to efficiently manipulate the traffic flow and reduce the cost in logistics by using the state of the art technologies which combine telecommunication, sensor, and control technology. Especially, the hardware part of ITS is rapidly adapting to the up-to-date techniques in GPS and telematics to provide essential raw data to the controllers. However, the software part of ITS needs more sophisticated techniques to take care of vast amount of on-line data to be analyzed by the controller for their decision makings. In this paper, the authors develop a traffic congestion prediction model based on several different parameters from the sensory data captured in the Vehicle Detection System (VDS). This model uses the neural network technology in analyzing the traffic flow and predicting the traffic congestion in the designated area. This model also validates the results by analyzing the errors between actual traffic data and prediction program.

• Korean Journal of Remote Sensing
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• v.32 no.4
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• pp.365-382
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• 2016

The results from the Global Positioning System (GPS) measurements of the Mobile Observation Vehicle (MOVE) on the eastern coast of Korea have been compared with REFerence (REF) values from the fixed GPS sites to assess the performance of Precipitable Water Vapor (PWV) retrievals in a kinematic environment. MOVE-PWV retrievals had comparatively similar trends and fairly good agreements with REF-PWV with a Root-Mean-Square Error (RMSE) of 7.4 mm and $R^2$ of 0.61, indicating statistical significance with a p-value of 0.01. PWV retrievals from the June cases showed better agreement than those of the other month cases, with a mean bias of 2.1 mm and RMSE of 3.8 mm. We further investigated the relationships of the determinant factors of GPS signals with the PWV retrievals for detailed error analysis. As a result, both MultiPath (MP) errors of L1 and L2 pseudo-range had the best indices for the June cases, 0.75-0.99 m. We also found that both Position Dilution Of Precision (PDOP) and Signal to Noise Ratio (SNR) values in the June cases were better than those in other cases. That is, the analytical results of the key factors such as MP errors, PDOP, and SNR that can affect GPS signals should be considered for obtaining more stable performance. The data of MOVE can be used to provide water vapor information with high spatial and temporal resolutions in the case of dramatic changes of severe weather such as those frequently occurring in the Korean Peninsula.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.373-380
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• 2005

Mobile Mapping Systems are effective systems to acquire the position and image data using vehicle equipped with the GPS (Global Positioning System), IMU (Inertial Measurement Unit), and CCD camera. They are used in various fields of road facility management, map update, and etc. In the general photogrammetry such as aerial photogrammetry, GCP (Ground Control Point)s are needed to compute the image exterior orientation elements (the position and attitude of camera). These points are measured by field survey at the time of data acquisition. But it costs much time and money. Moreover, it is not possible to make sufficient GCP as much as we want. However Mobile Mapping Systems are more efficient both in time and money because they can obtain the position and attitude of camera at the time of photographing. That is, Image Orientation Technique must use GCP to compute the image exterior orientation elements, but on the other hand Direct Georeferencing can directly compute the image exterior orientation elements by GPS/INS. In this paper, we analyze about the positional accuracy comparison of ground point using the Image Orientation Technique and Direct Georeferencing Technique.

• Journal of the Society of Disaster Information
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• v.13 no.1
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• pp.96-105
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• 2017

Global warming, mainly caused by CO2, is one of the on­going cataclysms of the human race. The nation­wide policy to reduce greenhouse gases (GHG) has been enforced, for which it is crucial to estimate reliable GHG emissions. The unit load of road­section CO2 emission (URSCE) is a prerequisite for the evaluation of GHG emissions from road mobile source, and it is mainly computed using vehicular velocity source. Unfortunately, there is real­world limitations to collect and analyse representative speed data for nation­wide road network. To tackle this problem, a method for the evaluation of URSCE, proposed in this study, is based on a disaggregated way using big GPS vehicle data. The method yields more accurate URSCE than an current aggregated data based approach and can be directly employed for nation­wide road systems.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.71-78
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• 2010

The road safety depend on many road factors like vertical alignment, horizontal alignment and road cross section angle. These data are hardly to get with drawings, and the real data are differ from drawings because of road pavement overlay, etc. To get these data, so many time and cost are needed, moreover it is dangerous work in heavy traffic road. In this study we obtained the road safety data with RoSSAV(Road Safety Survey & Analysis Vehicle) of Korea Institute of Construction Technology in accordance with traffic flow, and make analysis of road safety with the vertical alignment, horizontal alignment and road cross section angle data. We derived the safety improvement method in Young-dong accident prone spot and described detail method in this paper.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.771-783
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• 2012

This paper proposes a scheme to collect video data of the vehicle black box in order to strengthen the public safety. The existing schemes, such as surveillance system with the fixed CCTV and car black box, have privacy issues, network traffic overhead and the storage space problems because all video data are sent to the central server. In this paper, the central server only collects the video data related to the accident or the criminal offense using the GPS information and time in order to investigation of the accident or the criminal offense. The proposed scheme addresses the privacy issues and reduces network traffic overhead and the storage space of the central server since the central server collects the video data only related to the accident and the criminal offense. The implementation and experiment shows that our service is feasible. The proposed service can be used as a component of remote surveillance system to prevent the criminal offense and to investigate the criminal offense.

• Spatial Information Research
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• v.14 no.2 s.37
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• pp.235-244
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• 2006

The MMS(Mobile Mapping System) using the vehicle equipped GPS, IMU and CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. The image, vehicle's 3 dimensional position and attitude information provided MMS is a important source for positioning objects included the image. In this research we applied the tracking technique to the specific object in image. The extraction of important object from immense MMS data makes more effectiveness in this system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.241-244
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• 2009

Recently car navigation systems which are widely spreaded and provide routes exactly have been evolved. The systems use various information and techniques as follows. In order to provide shortest path with good flow, realtime traffic information provided by DMB is used. Augmented reality technique is also introduced to give the sense of real to driver by displaying real images captured by camera during driving. But these operate well when the GPS receives data normally. Exact information about the position of vehicles becomes a base that supports the above function with realities. This paper proposes a method for compensating a given path. It uses various information by integrated vehicle networks when the GPS does not operates normally.