• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.293-294
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• 2022

In recent years, the maritime industry system including port facilities, VTS(Vessel traffic service) is rapidly evolving with the development of technology. The connection between systems has been greatly expanded, and many research cases using this connectivity have been reported. This paper deals with the structural design of the arrival/departure support system for an autonomous ship. The system requires navigation data from the autonomous ship and radar/AIS data from the port. In this paper, design result on how the arrival/departure support system interacts with the autonomous ship and port system are addressed.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.116-129
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• 2023

Recently, interest in autonomous driving has drawn attention to autonomous cooperative driving, which considers the development of driving technology of autonomous vehicles and the development of infrastructure that constitutes a driving environment. According to the concept of autonomous cooperative driving, This study analyzes the new infrastructure for autonomous driving that can complement the information of existing precise road maps and adding HD map layer as the new infrastructure. The new infrastructure for autonomous driving presented two types of improved facilities and one type of sensor only facility. Analysis of HD maps shows that information such as junction points rarely changes, but it is expected that infrastructure for autonomous driving can be added to convey the meaning of paying attention to obstacles that may arise at the junction. In this way, the new infrastructure for autonomous driving needs to support the roles of guidance, instruction, and attention that existing road facilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.165-167
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• 2011

Autonomous robots are intelligent machines that are capable of performing task in the world themselves with little or no human intervention. One of the main reason autonomous robots gained popularity in human's world is their ability to perform task with high degree of precision, accuracy and also consistency. One of the most studied fields in autonomous robot is the ability of decision making in robots. To tackle the ability of robots to make decision, this paper proposed an Autonomous Maze Solving Robot that is able to solve a maze using the optimum solution. The maze and the design of the robot are in compliance with IEEE Micromouse competition rules and regulation. Micromouse is an autonomous maze solving robot that shall be able to explore a maze on its own from a predefined starting location and find the optimum path to reach the predefined goal in the maze without human's intervention.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.491-502
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• 2022

Purpose: The purpose of this study is to find factors affecting the acceptance intention of autonomous mobility service by applying the unified technology acceptance theory(UTAUT). Methods: The measurement items for each component of this study were modified to meet the purpose of the study by referring to previous studies related to mobility based on UTAUT, which has secured validity and reliability in many studies. The collected data through the online survey were analyzed using hierarchical regression analysis. Results: It was found that performance expectation, effort expectation, social influence, and facilitation conditions for autonomous mobility service had a positive effect on acceptance intention. Also, in this relationship, it was confirmed that driving experience moderated the relationship between performance expectation and acceptance intention, and between effort expectation and acceptance intention. Conclusion: Understanding the public's acceptance of autonomous mobility services, and suggesting strategic implications for the direction of service development to companies that are pushing to enter the autonomous mobility service market.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.190-201
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• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.152-152
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• 2000

In this paper, we propose a new approach to intelligent motion and autonomous maneuvering of mobile robots using hybrid system. In high Level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot as a low vevel are specified in the abstracted motions, The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments.

• Journal of the Korea Society for Simulation
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• v.8 no.1
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• pp.89-99
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• 1999

The major objective of this research is to propose a design architecture for autonomous defense systems for supporting highly intelligent behavior by combining decision, perception, and action components. Systems with such high levels of autonomy are critical for advanced battlefield missions. By integrating a plenty of advanced modeling concepts such as system entity structure, endomorphic modeling, engine-based modeling, and hierarchical encapsulation & abstraction principle, we have proposed four layered design methodology for autonomous defense systems that can support an intelligent behavior under the complicated and unstable warfare. Proposed methodology has been successfully applied to a design of autonomous tank systems capable of supporting the autonomous planning, sensing, control, and diagnosis.

• Journal of the Korean Mathematical Society
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• v.49 no.4
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• pp.703-713
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• 2012

In this paper we study ${\omega}$-limit sets and attraction of non-autonomous discrete dynamical systems. We introduce some basic concepts such as ${\omega}$-limit set and attraction for non-autonomous discrete system. We study fundamental properties of ${\omega}$-limit sets and discuss the relationship between ${\omega}$-limit sets and attraction for non-autonomous discrete dynamical systems.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.58-65
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• 2003

This paper studies a steering control method using a neural network algorithm for an intelligent autonomous driving robot. Previous horizontal steering control methods were made by various possible situation on the road. However, it isn't possible to make out algorithms that consider all sudden variances on the road. In this paper, an intelligent steering control algorithm for an autonomous driving robot system is presented. The algorithm is based on Self Organizing Maps(SOM) and the feature points on the road are used as training datum. In a simulation test, it is available to handle a steering control using SOM for an autonomous steering control. The algorithm is evaluated on an autonomous driving robot. The algorithm is available to control a steering for an autonomous driving robot with better performance at the experiments.

• Current Industrial and Technological Trends in Aerospace
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• v.6 no.2
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• pp.143-153
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• 2008

This paper describes the current research trend and future development direction of autonomous flight of the aircraft. The autonomous flight means that aircraft control system recognize and cope with the emergency situation confronted during the flight by itself. Current research for autonomous flight technology is mainly performed for the application to unmanned air vehicle. Considering advent of future air traffic management system and increasing demand of the unmanned air vehicle application, however, autonomous flight technology required to be combined with future air traffic management system. In this paper, the current air traffic management system and anticipating change in future air traffic management system was investigated and research activities of autonomous flight technology was described as well as future prospect.