• Journal of KIISE:Databases
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• v.33 no.3
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• pp.283-298
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• 2006

The TPR-tree is the time-parameterized indexing scheme that supports the querying of the current and projected future positions of such moving objects by representing the locations of the objects with their coordinates and velocity vectors. If this index is, however, used in environments that directions and velocities of moving objects, such as vehicles, are very often changed, it increases the communication cost between the server and moving objects because moving objects report their position to the server frequently when the direction and the velocity exceed a threshold value. To preserve the communication cost regularly, there can be used a manner that moving objects report their position to the server periodically. However, the periodical position report also has a problem that lineal time functions of the TPR-tree do not guarantee the accuracy of the object's positions if moving objects change their direction and velocity between position reports. To solve this problem, we propose the query processing scheme and the data structure using road networks for predicting uncertainty positions of moving objects, which is reported to the server periodically. To reduce an uncertainty of the query region, the proposed scheme restricts moving directions of the object to directions of road network's segments. To remove an uncertainty of changing the velocity of objects, it puts a maximum speed of road network segments. Experimental results show that the proposed scheme improves the accuracy for predicting positions of moving objects than other schemes based on the TPR-tree.

• Journal of Korean Society of Forest Science
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• v.97 no.6
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• pp.656-660
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• 2008

This study is carried out to minimize the damage to the forest road when locating strip roads in the future for stability of timberland after afforestation by assessing the factors that affect the damage on the forest road surface and making appropriate constructing standards. Major factors that influence damage to the strip road surface were location, longitudinal gradients, soil types, cross-section shape in order of influence on damage. it is considered that structural road factors like longitudinal gradients, road width, location factors such as construction location, slope gradients and road material like soil types were greatly related to occurrence of road surface damage. Damage occurrences in the forest road were severe at the valley, longitudinal gradients of over 24%, weathered granite soil, concave of road position, road width of over 3.0 m. stability was high at longitudinal gradients of 4~24%, road width of under 3.0 m, ridge of road position, straight slope, soil materials. The evaluation table of damage possibility on forest road was manufactured by discriminant analysis using Quantification theory(II). The results showed that the discriminant ratios was 79.4% and this table was available for forest manager.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.35.4-35
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• 2001

Image detection system for road traffic data analysis is a real time detection system using image processing techniques to get the real-time traffic information which is used for traffic control and analysis. One of the most important functions in this system is to match the coordinates of real world and that of image on video camera. When there in no way to know the exact position of camera and it´s height from the object. If some points on the road of real world are known it is possible to calculate the coordinates of real world from image.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.8
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• pp.720-728
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• 2012

It is important for identification of noise and vibration problem of tire to consider influence of interaction between road and tire. A quantification of road noise is a challenging issue in vehicle NVH due to extremely complicated transfer paths of road noise as well as the difficulty in an experimental identification of input force from tire-road interaction. A noise caused by tire is divided into road noise(structure-borne noise) and pattern noise(air-borne noise). Pattern noise is caused by pattern shape of tire, which has larger than 500 Hz, but road noise is generated by the interactions between a tire and a vehicle body. In this paper, we define the quantitative analysis for road noise caused by interactions between tire and road parameters. For the identification of road noise, the chassis dynamometer that is equipped $10mm{\times}10mm $ square cleat in the semi-anechoic chamber is used, and the tire spindle forces are measured by load cell. The vibro-acoustic transfer function between ear position and wheel center was measured by the vibro-acoustic reciprocity method. In this study three tires with different type of mechanical are used for the experiment work.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.221-224
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• 2007

MMS(Mobile Mapping System) generates a efficient image data for mapping and facility management. However, this image data of MMS has many difficulties in a practical use because of huge data volume. Therefore the important information likes road sign post must be extracted from huge MMS image data. In Korea, there is the HMS(Highway Management System) to manage a national road that acquire the line and condition of road from the MMS images. In the HMS each road sign information is manually inputted by the keyboard from moving MMS. This manually passive input way generate the error like inaccurate position, mistaking input in this research we developed the automatic road sign identifying technique using the image processing and the direct geo-referencing by GPS/INS data. This development brings not only good flexibility for field operations, also efficient data processing in HMS.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.5
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.429-432
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• 1996

An x-ray astronomy experiment consisting of three collimated proportional counters and an X-ray Sky Monitor (XSM) was flown aboard the Indian Satellite IRS-P3 launched on March 21, 1996 from SHAR range in India. The Satellite is in a circular orbit of 830 km altitude with an orbital inclination of $98^{\circ}$ and has three axis stabilized pointing capability. Each pointed-mode Proportional Counter (PPC) is a multilayer, multianode unit filled with P-10 gas ($90\%$ Ar + $10\%\;CH_4$) at 800 torr and having an aluminized mylar window of 25 micron thickness. The three PPCs are identical and have a field of view of $2^{\circ}{\times}2^{\circ}$ defined by silver coated aluminium honeycomb collimators. The total effective area of the three PPCs is about 1200 $cm^2$. The PPCs are sensitive in 2-20 keV band. The XSM consists of a pin-hole of 1 $cm^2$ area placed 16 cm above the anode plane of a 32 cm$\times$32 cm position sensitive proportional counter sensitive in 3-8 keV interval. The position of the x-ray events is determined by charge division technique using nichrome wires as anodes. The principal objective of this experiment is to carry out timing studies of x-ray pulsars, x-ray binaries and other rapidly varying x-ray sources. The XSM will be used to detect transient x-ray sources and monitor intensity of bright x-ray binaries. Observations of black-hole binary Cyg X-1 and few other binary sources were carried out in early May and July-August 1996 period. Details of the x-ray detector characteristics are presented and preliminary results from the observations are discussed.

• International Journal of Highway Engineering
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• v.19 no.1
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• pp.107-119
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• 2017

PURPOSES : The desire of drivers to increase their driving speeds is increasing in response to the technological advancements in vehicles and roads. Therefore, studies are being conducted to increase the maximum design speed in Korea to 140 km/h. The stopping sight distance (SSD) is an important criterion for acquiring sustained road safety in road design. Moreover, although the perception-reaction time (PRT) is a critical variable in the calculation of the SSD, there are not many current studies on PRT. Prior to increasing the design speed, it is necessary to confirm whether the domestic PRT standard (2.5 s) is applicable to high-speed driving. Thus, in this study, we have investigated the influence of high-speed driving on PRT. METHODS : A driving simulator was used to record the PRT of drivers. A virtual driving map was composed using UC-Win/Road software. Experiments were carried out at speeds of 100, 120, and 140 km/h while assuming the following three driving scenarios according to driver expectation: Expected, Unexpected, and Surprised. Lastly, we analyzed the gaze position of the driver as they drove in the simulated environment using Smarteye. RESULTS : Driving simulator experimental results showed that the PRT of drivers decreased as driving speed increased from 100 km/h to 140 km/h. Furthermore, the gaze position analysis results demonstrated that the decrease in PRT of drivers as the driving speed increased was directly related to their level of concentration. CONCLUSIONS : In the experimental results, 85% of drivers responded within 2.0 s at a driving speed of 140 km/h. Thus, the results obtained here verify that the current domestic standard of 2.5 s can be applied in the highways designated to have 140 km/h maximum speed.

• 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.