• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.115-118
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• 2012

다양한 네트워크에서 군집을 분석하고 그 구조를 발견하는 것은 그 네트워크의 복잡도를 낮추어 전체 시스템을 이해하고 관리하는데 중요하다. 특히 기본적인 컴퓨팅이 가능한 여러 기기들이 자율적으로 서로 통신하여 군집을 이루는 자율 군집 네트워크에서 군집을 정확하게 발견하는 것은 집단행동 서비스를 실현하는데 있어서 중요한 기술이다. 따라서 본 연구에서는 자율 군집 네트워크에서 군집 탐지 기법을 제안한다. 제안하는 기법은 군집을 발견하고 그 군집을 식별하기 위해 해당 네트워크에서 한 노드를 공유하는 두 개의 간선 쌍에 대해 계층 군집화를 수행하고 계층 간에 간선 유사도를 계산하여 비교한다. 계층 군집화를 통한 간선들은 트리 구조로 표현할 수 있으며 최적의 분할 밀도를 이용하여 노드들을 클러스터링한 후 최종 군집으로 분리 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.184-185
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• 2022

국제해사기구(IMO)에서는 2017년 미래선박으로서 자율운항선박(MASS)의 개념을 채택한 바 있으며, 실해역 운항을 위한 국제법규 및 규정 검토를 진행하고 있다. 무인선은 악천후시 유인선이 수행하기 힘든 임무를 대체하거나 지원하기 위하여 원격 혹은 자율적으로 운용되는 일종의 소형 자율운항선박을 의미한다. 선박해양플랜트연구소에서는 2011년부터 해양수산부 연구개발사업을 통하여, 무인선 아라곤호 시리즈를 개발하였으며, 아라곤1호, 2호, 3호 등 총 3척을 운용하고 있다. 해당 선박은 길이 8미터, 배수량 약 3톤급의 활주선형으로 원격운항, 경로추종 및 충돌회피 등 자율운항 기능이 적용되어 있다. 한편, 무인선은 공중 드론과 달리 탑재중량이 크고, 항속시간이 길어 해상에서 감시,첩보, 정찰 등에 효용성이 높으며, 최근 한척보다는 여러 척을 운용하는 것이 효과적이어서 무인선 군집(USV Swarm)으로 해상임무를 수행하려는 연구가 다양하게 진행되고 있다. 선박해양플랜트연구소에서는 2019년부터, 기존의 아라곤호 시리즈 무인선들을 활용하여, 무인선 군집 자율운항 시스템 개발을 위한 "인공지능 기반 무인선 상황인식 및 자율운항 기술 개발" 과제를 진행하고 있다. 해상에서 불법선박이 출현시 이를 효과적으로 단속하기 위하여 추적 기동이 필요한데, 본 연구에서는 무인선 3척을 활용하여 불법선박을 추적하는 해상 감시 실해역 시험을 수행하였다. 본 논문에서는 무인선 군집 자율운항 시스템에 대하여 소개하고, 무인선 군집을 활용한 불법선 추적에 관한 실해역 시험결과에 대해 소개한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.4
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• pp.107-121
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• 2017

This study conducted a 3-stage survey and simulation experiment to identify the impact of vehicle platoons on car-following behavior of manually-driven vehicles. Vehicle maneuvering data obtained from driving simulations was statistically analyzed based on three measures including average speed, acceleration noise, and offset to represent the deviation of lateral movements. Results indicate that MV drivers tended to have psychological burden while driving in automated vehicle platooning environments, which resulted in different vehicle maneuvers. It is expected that the outcome of this study would be useful fundamentals in developing various traffic operations strategies for managing mixed traffic stream consisting of MVs and autonomous vehicles.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.698-701
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• 2020

여러 대의 자율주행 차량이 하나의 그룹을 형성하여 주행하는 군집주행은 미래 고속도로 교통 시스템의 핵심 기술이다. 이러한 군집주행에서 발생할 수 있는 다양한 상황에서의 안전을 고려하는 일은 단독 자율 주행에서의 경우보다 더 어렵다. 다양한 군집주행의 안전 위협 요인 중, 의도하지 않은 동작으로부터 자율주행 차량의 안전성을 향상하는 방법을 가이드하기 위하여 새로운 표준 ISO/PAS 21448이 제정되었다. 본 논문에서는 ISO/PAS 21448 표준이 다루는 시나리오를 통해 군집주행에서 발생할 수 있는 의도하지 않은 상황의 극복을 위한 방법을 제시하였다. 특히 군집주행 시뮬레이터인 VENTOS를 이용하여 본 논문에서 제시하는 방법이 안전한 군집주행이라는 목표를 달성할 수 있음을 확인하였다.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.332-347
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• 2017

Analysis of the interaction between the automated vehicles and manual vehicles is very important in analyzing the performance of automated cooperative driving environments. In particular, the automated vehicle platooning can affect the driving behavior of adjacent manual vehicles. The purpose of this study is to analyze the lane change behavior of the manual vehicles in automated vehicle platonning environment and to conduct the experiment and questionnaire surveys in three stages. In the first stage, a video questionnaire survey was conducted, and responsive behaviors of manual vehicles were investigated. In second stage, the driving simulator experiments were conducted to investigate the lane change behaviors of in automated vehicle platonning environments. To analyze the lane change behavior of the manual vehicles, lane change durations and acceleration noise, which are indicators of traffic flow stability, were used. The driving behavior of manual vehicles were compared across different market penetration rates (MPR) of automated vehicles and human factors. Lastly, NASA-TLX (NASA Task Load Index) was used to evaluate the workload of the manual vehicle drivers. As a result of the analysis, it was identified that manual vehicle drivers had psychological burdens while driving in automated vehicle platonning environments. Lane change durations were longer when the MPR of the automated vehicles increased, and acceleration noise were increased in the case of 30-40 years old or female drivers. The results from this study can be used as a fundamental for more realistic traffic simulations reflecting the interaction between the automated vehicles and manual vehicles. It is also expected to effectively support the establishment of valuable transportation management strategy in automated vehicle environments.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.67-85
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• 2018

Vehicle platooning through wireless communication and automated driving technology has become realized. Platooning is a technique in which several vehicles travel at regular intervals while maintaining a minimum safety distance. Truck platooning is of keen interest because it contributes to preventing truck crashes and reducing vehicle emissions, in addition to the increase in truck flow capacity. However, it should be noted that interactions between vehicle platoons and adjacent manually-driven vehicles (MV) significantly give an impact on the performance of traffic flow. In particular, when vehicles entering from on-ramp attempt to merge into the mainstream of freeway, proper interactions by adjusting platoon size and inter-platoon spacing are required to maximize traffic performance. This study developed a methodology for establishing operational strategies for truck platoonings on freeway on-ramp areas. Average speed and conflict rate were used as measure of effectiveness (MOE) to evaluate operational efficiency and safety. Microscopic traffic simulation experiments using VISSIM were conducted to evaluate the effectiveness of various platooning scenarios. A decision making process for selecting better platoon operations to satisfy operations and safety requirements was proposed. It was revealed that a platoon operating scenario with 50m inter-platoon spacing and the platoon consisting of 6 vehicles outperformed other scenarios. The proposed methodology would effectively support the realization of novel traffic management concepts in the era of automated driving environments.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.370-376
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• 2002

인터넷 환경에서 발생되는 수많은 데이터를 지능적으로 처리할 수 있는 자동화된 분석 시스템의 필요성이 제기된다. 이러한 시스템의 데이터 분석은 크게 지도 학습과 자율 학습으로 나된다. 본 논문에서는 특히 자율학습 군집화에 대한 자동화된 시스템으로서 지능화된 데이터 마이닝 에이전트를 제안한다. 군집화 과정에서는 데이터를 분석하는 분석가가 군집화의 방법과 결과 해석에 실시간으로 관여하기 어렵기 때문에 이러한 작업을 담당하는 지능화된 에이전트가 자동화된 군집화를 담당하면 효과적인 군집화 전략이 될 수 있다. 본 논문의 자동 군집화를 위한 지능화된 데이터 마이닝 에이전트 시스템은 군집화 수행 에이전트와 군집화 성능 평가 에이전트로 구성된 다중 에이전트로서 두 개의 에이전트가 서로 정보를 교환하면서 최적의 군집화를 수행한다. UCI Machine Repository 데이터를 이용한 실험을 통해 제안 시스템의 성능 평가를 수행하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.325-328
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• 2018

With the rapid development of autonomous driving technology, commercialization of freight cars and buses as well as passenger cars has come to the near future. As researches for commercialization of autonomous navigation are being actively carried out in various countries around the world, in accordance with the development of technology, this paper proposes a bus adopting a new concept of community driving technology based on C-V2X for more effective autonomous driving of buses do. In order to realize the cluster bus, we propose a more effective cluster bus using C-V2X, which is the core communication of the cluster driving, which is complementary to the existing V2X for inter-vehicle communication and vehicle-to-infrastructure communication.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.195-202
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• 2017

Unmanned Aerial Vehicles (UAV) have mostly been used for military purposes but with the progress in ICT and reduced manufacturing costs, they are increasingly used for various private services. UAVs are expected to carry out autonomous flying in the future. In order to carry out complex tasks, swarm flights are essential. Although the swarm flights has been researched a lot due to its different network and infrastructure from the existing UAV system, There are still not enough study on security threats and requirements for the secure swarm flights. In this paper, to solve these problems, UAV autonomous flight technology is defined based on US Army Corps of Engineers (USACE) and Air Force Research Laboratory (AFRL), and swarm flights and security threat about it are classified. And then we defined and compared security requirements according to security threats of each swarm flights so as to contribute to the development of secure UAC swarm flights in the future.

• Journal of IKEEE
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• v.22 no.4
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• pp.1099-1103
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• 2018

Platooning of vehicles is an efficient traffic management model that improves traffic flow and fuel consumption. Especially, it is necessary to reduce computational load and networking overhead in automated connected vehicle systems. Because it is important to maintain the size of the platoon group appropriately for efficient platoon operation, this study proposed a dynamic grouping scheme for platooning in an automated vehicle system. The proposed scheme is analyzed by a mathematical model based on Markov chain. From the performance evaluation, it was confirmed that the proposed scheme appropriately controls the size of the platoon group.