• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.81-90
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• 2016

As an autonomous driving vehicle (AV) need to cope with external road conditions by itself, its perception performance for road environment should be better than that of a human driver. A vision sensor, one of AV sensors, performs lane detection function to percept road environment for performing safe vehicle steering, which relates to define vehicle heading and lane departure prevention. Performance standards for a vision sensor in an ADAS(Advanced Driver Assistance System) focus on the function of 'driver assistance', not on the perception of 'independent situation'. So the performance requirements for a vision sensor in AV may different from those in an ADAS. In assuming that an AV keep previous steering due to lane detection failure, this study calculated lane departure distances between the AV location following curved road alignment and the other one driving to the straight in a curved section. We analysed lane departure distance and time with respect to the allowance of lane detection malfunction of an AV vision sensor. With the results, we found that an AV would encounter a critical lane departure situation if a vision sensor loses lane detection over 1 second. Therefore, it is concluded that the performance standards for an AV should contain more severe lane departure situations than those of an ADAS.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.749-754
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• 2021

In order to solve problems such as a decrease in the agricultural population and an aging population, research on agricultural robots is being actively conducted for the purpose of automating various agricultural tasks. The harvesting process is the most labor-intensive process among farm work and this process consumes about 2-3 times more compared to other processes. Since the transport of agricultural crops requires the most labor costs and there is a risk of injury during the operation, automating the transport operation through an agricultural robot can improve safety and significantly improve productivity. Therefore, this paper proposes an agricultural robot that is optimized for farm worksites and capable of autonomous driving.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.242-244
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• 2012

자율 주행 할 수 있는 로봇은 사람이 갈 수 없는 위험한 장소이나 좁은 장소에 접근 할 수 있는 능력이 있다. 로봇에 광소자 센서를 이용하여 빛의 차이에 따라 스스로 길을 찾아 갈수 있게 하였다. 밝기에 따라 로봇이 길을 찾으므로 차선이나 도로의 지시 선을 따라 로봇이 원하는 목지에 도달 할 수 있게 하였다. 또한 무선 센서를 이용하여 임무 수행 중 얻은 데이터를 무선으로 전달 할 수 있게 하였다.

• Annual Conference of KIPS
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• 2017.11a
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• pp.510-513
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• 2017

자전거 이용자 급증으로 자전거의 도난 및 분실을 방지하여 사용자를 안심시켜주고 주행 중 위험요소를 줄이고자 하는 목소리가 높아지고 있다. 본 논문에서는 애플리케이션 개발을 위해 MCU(Micro Controller Unit)인 Arduino Mega 2560 기반에 블루투스(Bluetooth) 통신 방식을 사용하여 자전거 잠금장치, 위치 추적 장치를 조작하고 후방 감지 장치를 제어하였으며 초음파 거리센서 값을 이용하여 LED Strip 및 진동 모터로 사용자에게 주행 상태를 알리는 장치를 구현하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.265-269
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• 2006

본 논문에서는 간헐성 카오스를 이용한 장해물 회피 문제를 다루었다. 본 본문은 Chua's 방정식을 이용한 카오스 회로를 이동 로봇에 내장하여 카오스 이동 로봇을 구성하고 이 카오스 이동 로봇이 어느 임의 평면을 카오스 궤적을 가지고 주행하다가 고정 장애물, 또는 은닉 이동 장애물을 만나면 이를 회피하는 알고리즘을 제시하였다. 간헐성 카오스 로봇의 장애물 회피의 경우 고정 장애 and, 이동 장애물, 장애물 위험에 따른 로봇의 접근 등에서 잘 회피됨을 확인하였으며 만족할 만한 결과를 얻었다.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.19-29
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• 2019

Recently, autonomous vehicles have been studied actively. Autonomous vehicles can detect objects around them using their on board sensors, estimate collision probability and maneuver to avoid colliding with objects. Many algorithms are suggested to prevent collision avoidance. However there are limitations of complex and diverse environments because algorithm uses only the information of attached environmental sensors and mainly depends on TTC (time-to-Collision) parameter. In this paper, autonomous driving algorithm using I2V communication-based cooperative sensing information is developed to cope with complex and diverse environments through sensor fusion of objects information from infrastructure camera and object information from equipped sensors. The cooperative sensing based autonomous driving algorithm is implemented in autonomous shuttle bus and the proposed algorithm proved to be able to improve the autonomous navigation technology effectively.

• Annual Conference of KIPS
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• 2021.11a
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• pp.1112-1115
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• 2021

우리는 본 연구를 통해 최근 지속적으로 증가하고 있는 개인형 이동수단인 킥보드, 전기 자전거 등을 이용하는 사용자가 편리하고 안전한 주행을 할 수 있도록 AR 기술을 통해 길안내 서비스를 제공하는 방법 및 관련 기술, 그리고 IoT 기반으로 사용자가 착용한 웨어러블 기기와의 연동을 통해 주행 중 사고위험을 미리 인지할 수 있는 기술도 제안하였다. 우리가 제안한 기술과 서비스를 통해 최근 사회적 이슈가 되고 있는 개인형 이동수단으로 인한 안전사고 예방에 기여할 수 있을 것으로 기대해본다

• Annual Conference of KIPS
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• 2024.10a
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• pp.1057-1058
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• 2024

본 연구는 본인 인증 및 객체 탐지 알고리즘 기반의 보안 기능을 탑재한 배달 로봇을 제안한다. 기존 배달 로봇의 물품 도난 위험성 해결을 위한 보안 시스템 도입과 장애물 대처 및 강화학습 기반 경로계획 주행으로 보안성과 주행 안정성을 갖춘 배달 로봇을 고안하였다.

• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1221-1227
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• 2012

It is expected that the vehicle safety systems using vehicle-to-vehicle communication can reduce the possibility of vehicle collision and prevent the chain crash by promptly delivering the status of neighboring vehicles. Many IEEE 802.11 DCF based Flooding schemes have been proposed, but they may generally expose the problems that the transmission efficiency is sharply declined as the vehicle density has increased and then is related to the low possibility of the channel access. Therefore, this paper proposes a collision prevention scheme using adaptively controlling the frequency of the message exchanges based on the current status of neighboring vehicles. Moreover, it is shown from simulation that the proposed scheme provides the performance gains over the existing Flooding based scheme.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.375-380
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• 2022

High-speed railway bridges carry a risk of dynamic response amplification due to resonance caused by train loads, and running safety and riding comfort must therefore be reviewed through dynamic analysis in accordance with design codes. The running safety and ride comfort calculation procedure, however, is time consuming and expensive because dynamic analyses must be performed for every 10 km/h interval up to 110% of the design speed, including the critical speed for each train type. In this paper, a deep-learning-based prediction system that can predict the running safety and ride comfort in advance is proposed. The system does not use dynamic analysis but employs a deep learning algorithm. The proposed system is based on a neural network trained on the dynamic analysis results of each train and speed of the railway bridge and can predict the running safety and ride comfort according to input parameters such as train speed and bridge characteristics. To confirm the performance of the proposed system, running safety and riding comfort are predicted for a single span, straight simple beam bridge. Our results confirm that the deck vertical displacement and deck vertical acceleration for calculating running safety and riding comfort can be predicted with high accuracy.