• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.31-37
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• 2017

Recently, governmental authority and local government are looking for a method of utilizing location information of smart phone for urgent rescue in fire and kidnap situation. Under this background, in this study, a method of rapidly collecting, constructing location determination based Wi-Fi AP data utilizing location information of smart phone and mobile mapping system was suggested in order to construct precise positioning information that could be utilized under urgent situation. By performing compensation work for GPS/INS/DMI through collected outcome, position of collected vehicle was acquired. In addition, source data integrating Wi-Fi information and collected position by coupling based on Wi-Fi AP collector and GPS time was constructed and Wi-Fi radiomap was constructed by removing Wi-Fi signal noise that reduces precise position performance. As a result of performing location determination performance assess ment by selecting 10 test positions by each local government, result value of 25.46cm for total local government average and 27.76m for SD could be obtained. It is considered that this result could be utilized as a technology of being able to supplement or substituting GPS location determination technology that is impossible in plocation determination of mobile communication company's base station (200m~2km) and indoor being used at present.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.656-660
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• 2004

The Mobile Mapping System is an effective method to acquire the position and image data using vehicle equipped with the GPS (Global Positioning System), IMU (Inertial Measurement Unit), and CCD camera. It is 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 System is more efficient both in time and money because it can obtain the position and attitude of camera at the time of photographing. That is, Indirect Georeferencing 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 Direct Georeferencing and Indirect Georeferencing.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.71-78
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• 2012

The digital tachograph is a device that automatically records speed and distance of a vehicle, together with the driver's activity and vehicle status at an accident. It records vehicle speed, break status, acceleration, engine RPM, longitude and latitude of GPS, accumulated distance, and so on. European Commission regulation made digital tachographs mandatory for all trucks from 2005. Republic of Korea made digital tachographs mandatory for all new business vehicles from 2011 and is widening the range of vehicles that must install digital tachographs year by year. This device is used to analyze driver's daily driving information and car accidents. Under a car accident that makes the device reliability unpredictable, it is very important to store driving information with maximum reliability for its original mission. We designed and implemented a practical digital tachograph. This paper presents a storage scheme that consists of a first storage device with small capacity at a high reliability and a second storage device with large capacity at a low cost in order to reliably records data with a hardware at a low cost. The first storage device records data in a SLC NAND flash memory in a log-structured style. We present a reverse partial scan that overcomes the slow scan time of log-structured storages at the boot stage. The scheme reduced the scan time of the first storage device by 1/50. In addition, our design includes a scheme that fast stores data at a moment of accident by 1/20 of data transfer time of a normal method.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.553-562
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• 2017

GPS (Global Positioning System) receiver among various sensors mounted on UAV (Unmanned Aerial Vehicle) helps to perform various functions such as hovering flight and waypoint flight based on GPS signals. GPS receiver can be used in an environment where GPS signals are smoothly received. However, recently, the use of UAV has been diversifying into various fields such as facility monitoring, delivery service and leisure as UAV's application field has been expended. For this reason, GPS signals may be interrupted by UAV's flight in a shadow area where the GPS signal is limited. Multipath can also include various noises in the signal, while flying in dense areas such as high-rise buildings. In this study, we used analytical photogrammetry and auto tracking total station technique for 3D positioning of UAV. The analytical photogrammetry is based on the bundle adjustment using the collinearity equations, which is the geometric principle of the center projection. The auto tracking total station technique is based on the principle of tracking the 360 degree prism target in units of seconds or less. In both techniques, the target used for positioning the UAV is mounted on top of the UAV and there is a geometric separation in the x, y and z directions between the targets. Data were acquired at different speeds of 0.86m/s, 1.5m/s and 2.4m/s to verify the flight speed of the UAV. Accuracy was evaluated by geometric separation of the target. As a result, there was an error from 1mm to 12.9cm in the x and y directions of the UAV flight. In the z direction with relatively small movement, approximately 7cm error occurred regardless of the flight speed.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.117-126
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• 2014

Recently, due to various environmental problems such as global warming, increasing of international oil prices and exhaustion of resource, a paradigm of world automobile market is rapidly changing from vehicles using internal combustion engine to eco-friendly vehicles using electric power such as EV (Electric Vehicle), HEV (Hybrid Electric Vehicle), PHEV (Plug-in Hybrid electric Vehicle) and FCEV (Fuel Cell Electric Vehicle). There are many driving cycles for performance evaluation of conventional vehicles. However there is a lack of researches on driving cycle for EV. This study is composed of part 1 and part 2. In this paper part 1, in order to develop urban driving cycle for performance evaluation of electric vehicles, Gwacheon-city patrol route of police patrol car was selected. Actual driving test was performed using EV. The driving data such as velocity, time, GPS information etc. were recorded. GUDC-EV (Gwacheon-city Urban Driving Cycle for Electric Vehicles) including road gradient was developed through the results of analyzing recorded data. Reliability of the driving cycle development method was substantiated through comparison of electricity performance. In the second part of this study, the developed driving cycle was compared to simulation result of the existing urban driving cycle. Verification of the developed driving cycle for EV performance evaluation was described.

• KIISE Transactions on Computing Practices
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• v.22 no.4
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• pp.189-194
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• 2016

A trajectory is the motion path of a moving object. The advances in IT have made it possible to collect an immeasurable amount of various type of trajectory data from a moving object using location detection devices like GPS. The trajectories of moving objects are widely used in many different fields of research, including the geographic information system (GIS) field. In the GIS field, several attempts have been made to automatically generate digital maps of roads by using the vehicle trajectory data. To achieve this goal, the method to cluster the trajectories on the same road is needed. Usually, the $Fr{\acute{e}}chet$ distance measure is used to calculate the distance between a pair of trajectories. However, the $Fr{\acute{e}}chet$ distance measure requires prolonged calculation time for a large amount of trajectories. In this paper, we presented a fast heuristic algorithm to distinguish whether the trajectories are in close distance or not using the discrete $Fr{\acute{e}}chet$ distance measure. This algorithm trades the accuracy of the resulting distance with decreased calculation time. By experiments, we showed that the algorithm could distinguish between the trajectory within 10 meters and the distant trajectory with 95% accuracy and, at worst, 65% of calculation reduction, as compared with the discrete $Fr{\acute{e}}chet$ distance.

• Spatial Information Research
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• v.19 no.4
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• pp.73-79
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• 2011

With the recent increase in demand for geo-registered imagery, Mobile Mapping Systems(MMS), which can quickly construct geographic information, has become important. The main part of MMS is the high-precision observation system, which collects geographic information at a certain speed. MMS has a complex data generation process and requires a standard-specific vehicle for its use, limiting its application range. In this paper, lightweight MMS is proposed to overcome its complexity by replacing the time synchronizer with a high-speed camera and by stabilizing motion with MEMS IMU/GPS. The proposed low-cost, portable method is expected to produce of geo-registered imagery efficiently.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.151-157
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• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• International Journal of Highway Engineering
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• v.17 no.5
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• pp.75-82
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• 2015

PURPOSES : In link matching using vehicular trajectory in a car navigation system, it is technically difficult to match the location of the subject vehicle with a link on an electronic map in the vehicle on a grade separation highway segment consisting of an elevated highway and atgrade highway, because of the overlap of geometric lines of the two highways. This study was initiated to propose a link matching algorithm using the characteristics of vehicular movement of the subject vehicle. METHODS : The selected test site is the highway segment between Jeong-reung IC and Gil-eum IC where the Inner Circulation Road and Jeong-reung-ro run together. To evaluate the proposed algorithm, this study collected the raw packet data of vehicles that drove on the test site. In a simulation environment, link matching was performed using an existing algorithm as well as the proposed algorithm. RESULTS: It was clearly found that the characteristics of vehicular movements are different on the two highways. CONCLUSIONS: The proposed algorithm outperformed the existing algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1046-1052
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• 2016

For the safe driving of autonomous vehicles, accurate position estimation is required. Generally, position error must be less than 1m because of lane keeping. However, GPS positioning error is more than 1m. Therefore, we must correct this error and a map matching algorithm is generally used. Especially, road marking intensity map have been used in many studies. In previous work, 3D LIDAR with many vertical layers was used to generate a local intensity map. Because it can be obtained sufficient longitudinal information for map matching. However, it is expensive and sufficient road marking information cannot be obtained in rush hour situations. In this paper, we propose a localization algorithm using an accumulated intensity local map. An accumulated intensity local map can be generated with sufficient longitudinal information using 3D LIDAR with a few vertical layers. Using this algorithm, we can also obtain sufficient intensity information in rush hour situations. Thus, it is possible to increase the reliability of the map matching and get accurate position estimation result. In the experimental result, the lateral RMS position error is about 0.12m and the longitudinal RMS error is about 0.19m.