• 한국ITS학회 논문지
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• 제23권1호
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• pp.182-196
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• 2024

자동차 보급과 교통 시설 발달로 인한 문제에 대응하여, ADAS와 같은 운전 보조 기술이 주목받고 있다. 최근에는 스마트폰 내장 센서를 사용한 운전패턴 분석 방법론이 개발되었다. 이 연구에서는 레이블 없이 대조학습을 통해 운전패턴의 특징을 학습하고 변화점을 감지하는 새로운 방법을 제안한다. 이 방법은 운전패턴 분류에도 확장 가능하여, 매우 적은 레이블링 데이터만으로 높은 분류 성능을 달성할 수 있음은 물론 적용 차량이 달라지는 도메인 변화 문제에 민감하게 반응하지 않아 일반화된 성능을 달성할 수 있다는 장점을 가지고 있다. 또한 본 연구에서는 추후 스마트폰 적용성을 고려하여 6가지 대표적인 경량화 딥러닝 모델에 대해 제안하는 방법을 적용하고 비교분석하여 추후 스마트폰 기반의 시스템 개발에 활용할 수 있도록 하였다.

• 융합신호처리학회논문지
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• 제22권2호
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• pp.85-90
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• 2021

운전자의 안전 운전을 위한 첨단 운전자 보조시스템(ADAS; Advanced Driver Assistance System)은 자율주행 자동차에서 중요한 연구 분야 가운데 하나이다. 특히, 이전에 자동차에 부착된 영상센서를 기반으로 한 ADAS 소프트웨어는 구축 비용이 저렴하고 그 활용도가 우수하다. 본 논문에서는 선행차의 주행 상황을 인지할 수 있는 선행 차량 후미등(Tail-Lamp)의 정지등(Break-Lamp) 영역을 검출하는 알고리즘을 제안한다. 제안하는 방법은 주행 영상으로부터 객체 추적에 우수한 성능을 보이고 있는 YOLO 기술을 이용하여 자동차 객체를 추출하고, 추출된 자동차 관심 영역의 HSV 영상을 이용하여 정지등의 밝기 변화 영역을 검출한다. 그 다음 검출된 각 정지등 후보 고립영역을 라벨링하여 후보 영역들 간의 모양 대칭성을 인지하는 선택적 주의집중 모델(Selective Attention Model)을 적용하여 정지등 영역을 검출한다. 제안한 알고리즘의 성능 평가를 위하여 다양한 주행 영상에 적용하여 실험한 결과 ADAS에 적용 가능한 성공적인 검출 결과를 보였다.

• 한국기계가공학회지
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• 제12권1호
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• pp.70-76
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• 2013

Recently, the performance and function of electrical and electronic system in automotive vehicles is developing at a rapid rate with the advancement of IT technologies. Combined together with micro-controller and sensor technologies, the Vehicle Smart System (VSS) being developed to improve driver's convenience and comfort has been employed to a variety of applications. In addition to the convenience system, the Auto-parking Assistance System (AAS) that is now attracting a new attention has been already applied to some vehicles, but it is currently limited to luxury car models only. In this paper, we present a fuzzy controller that enables autonomous parking assistance without the AAS. The controller can perform the assistance with information provided from moving status, current position and steering angle as one is able to park a car based on his/her experience and knowledge for driving and parking. We have evaluated its performance of the proposed controller by simulation and tested the excellence of the controller by building a model vehicle embedded with the micro-controllers.

• 자동차안전학회지
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• 제7권3호
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• pp.30-34
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• 2015

This study examined the Korean drivers' acceptance of SAS(Speed Assistance systems) and traffic sign conditions in Korea roads for SLIF(Speed Limit Information Function) that is a part of SAS. Exceeding the speed limit is a factor in the severity of many road accidents and SAS would help the driver to observe a speed limit by warning and/or effectively limiting the speed of the vehicle. SAS are in the initial phase in Korea, Korean drivers could not be familiar with automatical speed limiting during driving, SAS interface design would be considered to be more readily acceptable to the public. And advanced SAS have been introduced onto the market which are able to inform the driver of the current speed limit based on camera and/or digital maps based SLIF. These systems are based on external data using sensors, so environmental conditions are an important factor which could cause malfunction of SLIF functions.

• 한국인터넷방송통신학회논문지
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• 제20권2호
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• pp.149-155
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• 2020

한국도로교통공단은 교통사고분석시스템(TAAS)을 활용하여 2015년부터 발생한 교통사고 원인을 분석한 통계를 제공하고 있다. 교통사고 발생 주요 원인으로, 2018년 한해 전체 교통사고 발생원인 중 전방주시 부주의가 대부분의 원인임을 TAAS를 통해 발표했다. 교통사고 원인에 대한 통계자료의 세부항목으로 운전 중 스마트폰 사용, DMB 시청 등의 안전운전 불이행 51.2%와 안전거리 미확보 14%, 보행자 보호의무 위반 3.6% 등으로, 전체적으로 68.8%의 비율을 보여준다. 본 논문에서는 Deep Learning의 알고리듬 중 CNN(Convolutional Neural Network)를 활용하여 첨단 운전자 보조 시스템 ADAS(Advanced Driver Assistance Systems)을 개선한 시스템을 제안하고자 한다. 제안된 시스템은 영상처리에 주로 사용되는 Conv2D 기법을 사용하여 운전자의 얼굴과 눈동자의 조향을 분류하는 모델을 학습하고, 차량 전방에 부착된 카메라로 자동차의 주변 object를 인지 및 검출하여 주행환경을 인지한다. 그 후, 학습된 시선 조향모델과 주행환경 데이터를 사용하여 운전자의 시선과 주행환경에 따라, 위험요소를 3단계로 분류하고 검출하여 운전자의 전방 및 사각지대 보조한다.

• 한국융합학회논문지
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• 제12권10호
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• pp.211-218
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• 2021

최근에 전동킥보드와 같은 개인형 이동수단의 보급이 급격히 확대되면서 교통사고 발생 건수도 크게 늘고있다. 개인형 모빌리티가 자세 안정성이 낮고 탑승자가 외부로 노출되어 전도 사고나 낙상 사고의 위험이 크기 때문이다. 전동킥보드 사고 방지를 위해 본 논문은 주행 보조 장치로써 자동긴급제동시스템과 안전시동시스템을 제안하였다. 인공지능 기반 물체 인식 기술을 이용하여 주변 위험 요소를 탐지하고 자동으로 제동을 걸 수 있는 시스템을 개발하였다. 또한 운전자의 탑승이 확인되기 전까지 장치의 시동을 보류하는 안전시동시스템도 개발하였다. 상용차와 주행 조건이 매우 다른 개인형 이동 수단에 특화된 첨단 운전자 보조 시스템 융합 기술을 제안한다는 점에서 본 연구의 의의가 있다.

• 대한인간공학회지
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• 제29권1호
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• pp.17-24
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• 2010

There has been recent interest in intelligent vehicle technologies, such as advanced driver assistance systems (ADASs) or in-vehicle information systems (IVISs) that offer a significant enhancement of safety and convenience to drivers and passengers. However, unsuitable design of HMI (Human Machine Interface) must increase driver distraction and workload, which in turn increase the chance of traffic accidents. Distraction in particular often occurs under a heavy driving workload due to multitasking with various electronic devices like a cell phone or a navigation system while driving. According to the 2005 road traffic accidents in Korea report published by the ROad Traffic Authority (ROTA), more than 60% of the traffic accidents are related to driver error caused by distraction. This paper suggests the structure of vehicle environment for real-time driving behavior monitoring system while driving which is can be used the driver workload management systems (DWMS). On-road experiment results showed the feasibility of the suggested vehicle environment for driving behavior monitoring system.

• ETRI Journal
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• 제45권2호
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• pp.240-253
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• 2023

Spatial information is geometrical information combined with the properties of an object. In city areas where unmanned aerial vehicle (UAV) usage demand is high, it is necessary to determine the appropriate driving altitude considering the height of buildings for safe driving. In this study, we propose a data-provision method that generates the driving altitude of UAVs with a pseudo-3D building model. The pseudo-3D building model is developed using high-precision spatial information provided by the National Geographic Information Institute. The proposed method generates the driving altitude of the UAV in terms of tile information, including the UAV's starting and arrival points and a straight line between the two points, and provides the data to users. To evaluate the efficacy of the proposed method, UAV driving altitude information was generated using data of 763 551 pseudo-3D buildings in Seoul. Subsequently, the generated driving altitude data of the UAV was verified in AirSim. In addition, the execution time of the proposed method and the calculated driving altitude were analyzed.

• Advances in Automotive Engineering
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• 제1권1호
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• pp.143-152
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• 2018

In this study an economical image stitching algorithm for use in automotive industry is developed for retrofittable panoramic image assistance applications. The aim of this project is to develop a driving assistance system known as Panoramic Parking Assistance (PPA) which is cheap, retrofittable and compatible for every type of automobiles. PPA generates bird's eye view image using cameras installed on the automobiles. Image stitching requires to get bird's eye view position of the vehicle. Panoramic images are wide area images that cannot be available by taking one shot, attained by stitching the overlapping areas. To achieve correct stitching many algorithms are used. This study includes some type of these algorithms and presents a simple one that is economical and practical. Firstly, the mathematical model of a wide view of angle camera is provided. Then distorted image correction is performed. Stitching is implemented by using the SIFT and SURF algorithms. It has been seen that using such algorithms requires complex image processing knowledge and implementation of high quality digital processors, which would be impracticle and costly for automobile use. Thus a simpler algorithm has been developed to decrase the complexity. The proposed algorithm uses one matching point for every couple of images and has ease of use and does not need high power processors. To show the efficiency, images coming from four distinct cameras are stitched by using the algorithm developed for the study and usability for automotive application is analyzed.

• 자동차안전학회지
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• 제6권2호
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• pp.29-35
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• 2014

Lane Keeping Assistance System(LKAS) is a kind of Advanced Driver Assistance Systems(ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in international committees such as ISO(the International Organization for Standardization). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP(Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System(LDWS). Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.