• 한국측량학회지
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• 제18권2호
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• pp.179-189
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• 2000

본 연구는 도시토지이용의 적합성분석을 실시하는데 있어 GSIS와 인공신경망의 유기적인 결합을 시도해 보았다. 인공신경망은 학습이라는 과정을 통해 신경망 노드(node)간의 연결강도를 합리적으로 결정할 수 있는 이점이 있다. 이러한 점에서 공간분석에서 요구되는 인자간의 경중률과 신경망의 연결강도는 대체가 가능하리라 판단된다. 본 연구를 수행하기 위해 두 종류의 신경망을 구성하였다. 1차 신경망은 토지이용별 적합성 분석에 적용했으며, 2차 신경망은 최적의 토지이용패턴을 분석하기 위해 구성하였다 이들 신경망은 C++로 작성된 프로그램에 의해 구현된 최급강하법에 의한 역전파 알고리즘에 의해 학습을 실시하였으며, 활성화 함수는 시그모이드 함수를 사용하였다. 분석결과는 현행 용도지역제에서 주거, 상업, 공업, 녹지에 대한 토지이용 적합도면과 4가지 유형의 토지이용에 대한 대상지역의 최적토지이용패턴을 제시한 도면으로서 Arc/Info의 Grid 형식으로 작성하였다. 또한 토지이용별 적합도면상에 나타난 적합지역과 최적토지이용패턴은 위치적인 면과 공간 구성에 있어 실제의 도시토지이용계획의 이론적인 개념에 매우 합치되는 분포형태를 보였다.

• 자동차안전학회지
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• 제13권4호
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• pp.14-19
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• 2021

This paper presents LiDAR static obstacle map based vehicle dynamic state estimation algorithm for urban autonomous driving. In an autonomous driving, state estimation of host vehicle is important for accurate prediction of ego motion and perceived object. Therefore, in a situation in which noise exists in the control input of the vehicle, state estimation using sensor such as LiDAR and vision is required. However, it is difficult to obtain a measurement for the vehicle state because the recognition sensor of autonomous vehicle perceives including a dynamic object. The proposed algorithm consists of two parts. First, a Bayesian rule-based static obstacle map is constructed using continuous LiDAR point cloud input. Second, vehicle odometry during the time interval is calculated by matching the static obstacle map using Normal Distribution Transformation (NDT) method. And the velocity and yaw rate of vehicle are estimated based on the Extended Kalman Filter (EKF) using vehicle odometry as measurement. The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment, and is verified with data obtained from actual driving on urban roads. The test results show a more robust and accurate dynamic state estimation result when there is a bias in the chassis IMU sensor.

• 대한기계학회논문집A
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• 제20권10호
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• pp.3160-3172
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• 1996

A search algorithm for the collision free, time optimal transport path of overhead cranes has been proposed in this paper. The map for the working environment of overhead cranes was constructed in the form of three dimensional grid. The obstacle occupied region and unoccupied region of the map has been represented using the octree model. The best-first search method with a suitable estimation function was applied to select the knot points on the collision free transport path to the octree model. The optimization technique, minimizing the travel time required for transporting objects to the goal while subjected to the dynamic constraints of the crane system, was developed to find the smooth time optimal path in the form of cubic spline functions which interpolate the selected knot points. Several simulation results showed that the selected estimation function worked effectively insearching the knot points on the collision free transport path and that the resulting transport path was time optimal path while satisfying the dynamic constraints of the crane system.

• 대한토목학회논문집
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• 제26권5B호
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• pp.511-517
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• 2006

홍수 피해는 인간에게 영향을 미치는 가장 중요하고 영향력 있는 자연재해 가운데 하나이다. 도시지역에서 국지적인 호우가 배수시스템의 용량을 초과할 경우 홍수피해가 발생된다. 도시지역에서 발생한 홍수는 도시산업과 교통 시스템을 마비시키며, 공공시설물에 막대한 피해를 야기시키다. 도시지역에서 이러한 피해를 줄이기 위해서는 도시지역의 복잡한 지형과 인위적인 배수시스템을 동시에 고려하기에 적합한 모형이 필요하다. 본 연구에서는 도시홍수의 침수범위, 침수심과 같은 홍수특성을 모의하기 위한 비정형격자기반 도시침수해석모형을 개발하였고, 이를 배수 시스템과 연계하였다. 본 연구를 통해 홍수 위험지역을 계산하고, 홍수대비지도를 만드는데 활용될 수 있다. 또한, 홍수담당기관의 의사지원시스템의 한 부분으로 활용되어 침수경감대책수립에 이용될 수 있다.

• 한국IT서비스학회지
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• 제19권1호
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• pp.113-127
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• 2020

Current web accessibility checks and automatic assessments have been pointed out that the assessment items and scores are evaluated from the developer's point of view rather than from the user's one. In addition, although most of the grades of an automatic assessment on the public web sites are excellent because they are built in accordance with the web accessibility development guidelines, not a few web sites shows relatively low grades in evaluating their usability test made by those users. Taking into account the inadequacy of these web accessibility assessments, this study has identified the differences between the grades of usability evaluations and automatic evaluations for people with low vision and analyzed the major factors affecting web accessibility usability evaluations using Repertory Grid Techniques. Also, the Hard Laddering method of the Means-End Chain theory was adopted to visualize the relationship between Attributes-Conferences-Value and a hierarchical value system analysis based on FGI(Focused Group Interview) to people with the low vision. This study proposed the measures to improve the current web accessibility automatic assessment allocation, expert evaluation criteria, and user task assessment. In particular, it is a web accessibility user evaluation model that can consider the web accessibility quality certification criteria and user review assessment by directly analyzing the user cognitive structure and value system. This study is expected to be useful as a research to enhance the quality of web accessibility assessment.

• Journal of Positioning, Navigation, and Timing
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• 제11권4호
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• pp.297-304
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• 2022

The models used for ionosphere error correction in positioning using Global Navigation Satellite System (GNSS) are representatively Klobuchar model and NeQuick model. Although these models can correct the ionosphere error in real time, the disadvantage is that the accuracy is only 50-60%. In this study, a method for polynomial modeling of Global Ionosphere Map (GIM) which provides Vertical Total Electron Content (VTEC) in grid type was studied. In consideration of Ionosphere Pierce Points (IPP) of satellites with a receivable elevation angle of 15 degrees or higher on the Korean Peninsula, the target area for model generation and provision was selected, and the VTEC at 88 GIM grid points was modeled as a polynomial. The developed VTEC polynomial model shows a data reduction rate of 72.7% compared to GIM regardless of the number of visible satellites, and a data reduction rate of more than 90% compared to the Slant Total Electron Content (STEC) polynomial model when there are more than 10 visible satellites. This VTEC polynomial model has a maximum absolute error of 2.4 Total Electron Content Unit (TECU) and a maximum relative error of 9.9% with the actual GIM. Therefore, it is expected that the amount of data can be drastically reduced by providing the predicted GIM or real-time grid type VTEC model as the parameters of the polynomial model.

• 한국컴퓨터정보학회논문지
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• 제24권9호
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• pp.83-95
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• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

• Journal of Positioning, Navigation, and Timing
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• 제13권1호
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• pp.85-92
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• 2024

This study develops a Global Positioning System (GPS) Code Multipath Grid Map (CMGM) of each individual domestic reference station from the extracted code multipath of measurement data. Multipath corresponds to signal reflection/refraction caused by obstacles around the receiver antenna, and it is a major source of error that cannot be eliminated by differencing. From the receiver-independent exchange format (RINEX) data for two days, the associated code multipath of a satellite tracking arc is extracted. These code multipath data go through bias correction and interpolation to yield the CMGM with respect to the azimuth and elevation angles. The effect of the CMGM on multipath mitigation is then quantitatively analyzed to improve the Root Mean Square (RMS) of averaged pseudo multipath. Furthermore, the single point positioning (SPP) accuracy is analyzed in terms of the RMS of the horizontal and vertical errors. During two weeks in February 2023, the RMSs of the averaged pseudo multipath for five reference stations decreased by about 40% on average after CMGM application. Also, the SPP accuracies increased by about 7% for horizontal errors and about 10% for vertical errors on average after CMGM application. The overall quantitative analysis indicates that the proposed approach will reduce the convergence time of Differential Global Navigation Satellite System (DGNSS), Real-Time Kinematic (RTK), and Precise Point Positioning (PPP)-RTK correction information in real-time to use measurement data whose code multipath is corrected and mitigated by the CMGM.

• 제어로봇시스템학회논문지
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• 제13권5호
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• pp.434-443
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• 2007

Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• 자동차안전학회지
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• 제16권2호
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• pp.20-26
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• 2024

The delivery using drones has been attracting attention because it can innovatively reduce the delivery time from the time of order to completion of delivery compared to the current delivery system, and there have been pilot projects conducted for safe drone delivery. However, the current drone delivery system has the disadvantage of limiting the operational efficiency offered by fully autonomous delivery drones in that drones mainly deliver goods to pre-set landing sites or delivery bases, and the final delivery is still made by humans. In this paper, to overcome these limitations, we propose obstacle detection and landing site selection algorithm based on a vision sensor that enables safe drone landing at the delivery location of the product orderer, and experimentally prove the possibility of station-to-door delivery. The proposed algorithm forms a 3D map of point cloud based on simultaneous localization and mapping (SLAM) technology and presents a grid segmentation technique, allowing drones to stably find a landing site even in places without prior information. We aims to verify the performance of the proposed algorithm through streaming data received from the drone.