• The Journal of Information Systems
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• v.31 no.3
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• pp.47-65
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• 2022

Purpose With the recent development of Big Data and Artificial Intelligence technology, self-driving technology has developed into three stages (partial self-driving) or four stages (conditional self-driving), it is expected to bring a new paradigm to transportation in the city. Although many researchers are researching related technologies, there is no research on self-driving for disabled persons. In this study, the basic research was conducted based on the assumption that the shared self-driving car used by the disabled person is similar to the special transportation currently driving. Design In this study, data analysis and machine learning techniques were utilized to analyze the mobility patterns of disabled persons by type and to search for leading factors affecting the traffic volume of special transportation. Findings The study found that external physical disorders and developmental disorders often visit general welfare centers, internal organ disorders often visit general hospitals, and the elderly and mental disorders have various destinations. In addition, machine learning analysis showed that the main transportation routes for the disabled person use arterial roads and auxiliary arterial roads and that the ratio of building usage-related variables affecting the use of special transportation for a disabled person is high. In addition, the distance to the subway and bus stops was also mentioned as a meaningful variable. Based on these analysis results, it is expected that the necessary infrastructure for shared self-driving cars for disability person traffic will be used as meaningful research data in the future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.159-164
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• 1995

Driving maneuver in car following are affected by not only the factors related to road structure and traffic condition, but also the factors related to driver's cognition to them. So the aim of this research this to model the relation of driver's cognition for car-following distance considering driver's fuzziness for imformation cognition, As a result, driver's cognition of car-following distance model with fuzzy number is proposed. The 'width', which characterizes the fuzzy number can introduce car-following informtion into the model.

• Journal of the Korean Society of Safety
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• v.23 no.3
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• pp.71-78
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• 2008

This study aims to identity the age group where driving performance significantly decreases based on the data collected from the Korea Transportation Safety Authority's driver aptitude tests in 2006. The test includes following six driving simulator-based tests: estimation of moving objects' speed, estimation of stopping distance, three tests for drivers' multi-task ability, and kinetic depth perception. These six test results were utilized for the identification of the age threshold applying the CART technique, suggesting driving ability significantly be decreased over 50s. This finding was confirmed by two analyses using the accident history data containing the information of accident and non-accident drivers and the degree of accident severity. The results of this study imply that accident prevention efforts should be enhanced over a wider range of age group than the current practice where the age of 65 is generally applied for the threshold dividing senior and non-senior driver groups.

• Journal of ILASS-Korea
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• v.18 no.3
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• pp.155-160
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• 2013

Worldwide harmonized light-duty vehicle test procedure (WLTP) for emission certification has been developed in WP.29 forum in UN ECE since 2007. The test procedure is expected to be applied to Korean light-duty diesel vehicles at the same time of adoption in Europe. The air pollutant emissions from light-duty vehicles have been regulated with weight per distance travelled which means the driving cycles can affect the results. The six Euro-5 light-duty diesel vehicles including sedan, SUV and truck have been tested with WLTP, NEDC which is used for emission certification for light-duty diesel vehicles, and CVS-75 to estimate how much particle number emission can be affected by different driving cycles. The averaged particle number emissions have not shown statistically meaningful difference. The maximum particle number emission have been found in Low speed phase of WLTP which is mainly caused by cooled engine conditions. The amount of particle number emission in cooled engine condition is much different as test vehicles. It means different technical solution is required in this aspect to cope with WLTP driving cycle.

• Current Optics and Photonics
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• v.3 no.2
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• pp.154-163
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• 2019

In this study, we developed an optical sighting system capable of shooting at a long-distance target by operating a digital gyro mirror composed of a gyro sensor and an FSM. The optical sighting system consists of a reticle part, a digital gyro mirror (FSM), a parallax correction lens, a reticle-ray reflection mirror, and a partial reflection window. In order to obtain the optimal volume and to calculate the leading angle range according to the driving angle of the FSM, a calculation program using Euler rotation angles and a three-dimensional reflection matrix was developed. With this program we have confirmed that the horizontal leading angle of the developed optical sighting system can be implemented under about ${\pm}8^{\circ}$ for the maximum horizontal driving angle (${\beta}={\pm}12.5^{\circ}$) of the current FSM. Also, if the ${\beta}$ horizontal driving angle of the FSM is under about ${\pm}15.5^{\circ}$, it can be confirmed that the horizontal direction leading angle can be under ${\pm}10.0^{\circ}$. If diagonal leading angles are allowed, we confirmed that we can achieve a diagonal leading angle of ${\pm}10.0^{\circ}$ with a vertical driving angle ${\alpha}$ of ${\pm}7.1^{\circ}$ and horizontal driving angle ${\beta}$ of ${\pm}12.5^{\circ}$.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.145-153
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• 2021

Automated Guided Vehicle (AGV) is commonly used in manufacturing plant, warehouse, distribution center, and terminal. AGV is self-driven vehicle used to transport material between workstations in the shop floor without the help of an operator, and AGV includes a material transfer system located on the top and driving system at the bottom to move the vehicle as desired. For navigation, AGV mostly uses lane paths, signal paths or signal beacons. Various predominant sensors are also used in the AGV. However, in the conventional AGV, there is a problem of not turning or damaging nearby objects or AGV in a narrow space. In this paper, a new driving system is proposed to move the vehicle in a narrow space. In the proposed driving system, two sets of the combined steering-drive unit are adopted to solve the above problem. A prototype of AGV with the new driving system is developed for the comparative analysis with the conventional AGV. In addition, the experimental result shows the improved performance of the new driving system in the maximum speed, braking distance and positioning precision tests.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.431-436
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• 2006

The latest system of GIS has been changing from 2 dimension to 3 dimension. According to the rapid growth of the fields linked to 3D GIS, 3D GIS has variously affected the public field, the national defense field, and the industrial field. This study estimated sight distance safety of curve section considering the environmental impact based on 3D GIS. Sight distance is calculated from the relation between road which keeps the three-dimension character and driver gaze, so it needs to consider both plane and vertical ior the accurate measuring. This study made analysis of the sight distance through considering the environmental impact with driving simulation of design speed 80km/h and running speed 60-120km/h.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.12
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• pp.1-12
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• 1996

A new local path planning algorithm using DPH (distance profile histogram) is suggested in this paper. The proposed method makes a grid type world map using distance values from multiple ultrasonic sensors and genrates local points through which the mobile robot can avoid obstcles safely. The DPH (distance profile historgram) represents geometrical arrangement of obstacles around the robot in the local polar coordinate system which is assumed to be atached to the robot. To control robot's navigation, a three-layered control structure is adopted. The proposed local path planning algorithm is placed on the top level. And a point-to-point translation controller takes the middle level. The bottom level consists of a velcoity servo and sonar driver modules which take charge of driving physical hardwares. The validity of the propsoed method is demonstated through several experiments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.88-93
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• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terns of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived form the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.