• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.511-517
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• 2006

Flood damage is one of the most important and influential natural disaster which has an effect on human beings. Local concentrated heavy rainfall in urban area yields flood damage increase due to insufficient capacity of drainage system. When the excessive flood occurs in urban area, it yields huge property losses of public facilities involving roadway inundation to paralyze industrial and transportation system of the city. To prevent such flood damages in urban area, it is necessary to develop adequate inundation analysis model which can consider complicated geometry of urban area and artificial drainage system simultaneously. In this study, an urban flood analysis model adopting the unstructured computational grid was developed to simulate the urban flood characteristics such as inundation area, depth and integrated with subsurface drainage network systems. By the result, we can make use of these presented method to find a flood hazard area and to make a flodd evacuation map. The model can also establish flood-mitigation measures as a part of the decision support system for flood control authority.

• Journal of Information Technology Services
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• v.19 no.1
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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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• v.11 no.4
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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.

• Journal of the Korea Society of Computer and Information
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• v.24 no.9
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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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• v.13 no.1
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.3
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• pp.177-182
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• 2004

A chill unit has been used to estimate chilling requirement for dormancy release and risk of freezing damage. A system that calculates chill units was developed to obtain site-specific estimates of dormancy release date for grapes and evaluated in Baekgu myun near Kimje City, Chunbuk, Korea from September 2002 to March 2003. The system utilized daily minimum and maximum temperature maps generated from spatial interpolation with temperature correction for topography. Hourly temperature was temporally interpolated from the daily data using a sine-exponential equation (Patron and Logan, 1981). Hourly chill units were determined from sigmoid, reverse sigmoid, and negatively increasing sigmoid functions based on temperature ranges and summed for 24 h. Cumulative daily chill units obtained from measurements did not increase until 20 October 2002, which was used as a start date for accumulation to estimate the dormancy release date. As a result, a map of dormancy release date in the study area was generated, assuming 800 chill units as a threshold for the chilling requirement. The chill unit accumulation system, implemented using Microsoft Visual Basic and C++ (Microsoft, Redmond, WA, USA), runs in the Windows environment with ArcView (ESRl Inc., Redlands, CA, USA).

• Journal of Korea Spatial Information System Society
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• v.3 no.2 s.6
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• pp.5-19
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• 2001

We are able to construct and utilize DEM(Digital Elevation Model) throughout the NGIS(National Geographic Information System) project. It is important that interpolation methods and appreciate size of grid for the construction of accurate DEM(Digital Elevation Model). There were several references related to the DEM(Digital Elevation Model) construction method, however they couldn't consider various topographical characteristics in the korea. In this study, we recommended that suitable interpolation method for each topographic element. After dividing Poonggi area into mountain, hill, urban, agricultural land, we constructed DEM(Digital Elevation Model) with various interpolation methods and grid size using 1:5,000 digital map. Then evaluated accuracy using elevation data which extracted from air-photo. The interpolation methods were analyzed and compared for various topographical conditions. As a result, Kriging method was superior to TIN method for all the topographical conditions. Another experiment was performed to examine optimal grid space for DEM with each topographical condition. 10m grid space was most suitable for mountain area and hilly districts, while 30m grid space was most suitable for urban area and farm land.