• 한국안전학회지
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• 제33권4호
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• pp.111-118
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• 2018

Korea is facing a surge in the aging population, showing that population aged 65 and above will be accounted for 42.5% of the total population in 2065 with the emphasis on the over-80 population consisting of 19.2%. In response to this abrupt change in population structure, the number of traffic fatality accident referring to older driver as aged 65+ years had been increasing from 605 fatalities in 2011 to 815 fatalities in 2015 resulting in increases in 34.7% in oppose to happening to decreases in 17.2% about non-older driver. With Logit analysis based on Newton-Raphson algorithm utilizing older driver's traffic fatality data for the 2011-2015 years, it was found that the likelihood of an accident resulting in a fatality for super older driver aged 80 years and above considerably increased compared to other older driver with aging classification: 2.24 times for violation of traffic lane, 2.04 times for violation of U-turn, 1.48 times for violation of safety distance, 1.35 times for violation of obstacle of passing; also average annual increase of traffic accident cost related to super older driver was fairly increased rather than other older driver groups. Hence, this study proposes that improving and amending transport safety system and Road Traffic Act for super older driver needs to be urgently in action about license management, safe driving education, etc. when considering the increase of over-80 population in the near future. Also, implementing a social agreement with all ages and social groups to apply with advanced driver assistance system for older driver groups will be able to become a critical factor to enhance safe driving over the face of the country.

• International Journal of Automotive Technology
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• 제1권2호
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• pp.61-69
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• 2000

This paper will address the basic requirements for realizing a stop and go cruise control system. Issues discussed comprise: functional, sensor and basic HMI requirements, primary characterization of naturalistic stop & go driving, and the basic approach of the transformation of situational knowledge in an elementary controller.

• 오토저널
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• 제26권4호
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• pp.26-31
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• 2004

ISO/TC204/WG14 is an International Leader in the Development and Production of Intelligent Transport Systems (ITS). WGl4, in Which Japan Serves as Chairman Country, is Responsible for the Standardization of Driver Assistance Systems (Vehicle/Roadway Warning and Control Systems). (omitted)

• 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.

• 디지털콘텐츠학회 논문지
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• 제15권5호
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• pp.579-586
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• 2014

본 논문은 문맥-자유 문법 (context-free grammar)를 이용하여, 차선변경 상황에서의 운전자의 행동패턴 인식을 하는 방법을 제안하는 것을 목표로 한다. 문맥-자유-문법은 기존 패턴인식 방식과는 대조적으로 유한적 기호로는 쉽게 표현될 수 없는 특징들을 비교적 손쉽게 표현할 수 있다. 이 방식을 적용하여, 동시에 여러 특징을 각각 고려해야 하는 좌표기반 데이터 처리 대신 심볼 시퀀스 방식 (symbolic sequence)을 패턴화하기 위해 구문론적 방식을 적용한다. 이 방법은 운전자와 안전 운전 분야 연구자들에게 효율적이고 보다 직관적인 방법으로 보다 더 효과적인 수행에 도움이 된다. 본 연구의 향후과제로 보다 안정적인 인식률을 획득하기 위해 확률적 구문분석 방법을 적용할 계획이다.

• 한국전자통신학회논문지
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• 제6권3호
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• pp.439-444
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• 2011

본 논문에서는 자동차에서 자동차의 속도, 엔진 회전속도, 연료, 엔진 온도, 연료 게이지, 회전표시등과 각종 경보 표시등 정보를 운전자에게 제공하는 차세대용 지능형 통합 스마트 모니터 시스템을 구현하였다. 구현한 지능형 스마트 HUD 모니터 시스템은 박막 트랜지스터 액정 표시 장치, 액정 표시 장치 배경 조명 발광 다이오드, 평면 미러, 특수 제작된 렌즈 및 구동회로로 구성되어 있으며, 운전자 안전성을 고려한 차세대 지능형 자동차 통합 HUD 시스템에 적용 가능함을 나타내었다.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.718-724
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• 2013

In today's automotive industry, there exist several systems that help drivers reduce the possibility of accidents, such as the ADAS (Advanced Driver Assistance System). The ADAS helps drivers make correct and quick decisions during dangerous situations. This study analyzed the performance of the IMM (Interacting Multiple Model) method based on multiple Kalman filters using the data acquired from a driving simulator. An IMM algorithm is developed to identify the current discrete state of neighboring vehicles using the sensor data and the vehicle dynamics. In particular, the driving modes of the neighboring vehicles are classified by the cruising and maneuvering modes, and the transition between the states is modeled using a Markovian switching coefficient. The performance of the IMM algorithm is analyzed through realistic simulations where a target vehicle executes sudden lane change or acceleration maneuver.

• 제어로봇시스템학회논문지
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• 제22권1호
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• pp.1-7
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• 2016

ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.

• 대한임베디드공학회논문지
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• 제10권5호
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• pp.325-333
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• 2015

Vision based night-time vehicle detection has been an emerging research field in various advanced driver assistance systems(ADAS) and automotive vehicle as well as automatic head-lamp control. In this paper, we propose night-time vehicle detection method based on multi-class support vector machine(SVM) that consists of thresholding, labeling, feature extraction, and multi-class SVM. Vehicle light candidate blobs are extracted by local mean based thresholding following by labeling process. Seven geometric and stochastic features are extracted from each candidate through the feature extraction step. Each candidate blob is classified into vehicle light or not by multi-class SVM. Four different multi-class SVM including one-against-all(OAA), one-against-one(OAO), top-down tree structured and bottom-up tree structured SVM classifiers are implemented and evaluated in terms of vehicle detection performances. Through the simulations tested on road video sequences, we prove that top-down tree structured and bottom-up tree structured SVM have relatively better performances than the others.

• International Journal of Contents
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• 제14권2호
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• pp.24-29
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• 2018

In this paper, we propose an efficient traffic light detection (TLD) method as an advanced driver assistance system (ADAS) for elderly drivers. Since an increase in traffic accidents is associated with the aging population and an increase in elderly drivers causes a serious social problem, the provision of ADAS for older drivers via TLD is becoming a necessary(Ed: verify word choice: necessary?) public service. Therefore, we propose an economical TLD method that can be implemented with a simple black box (built in camera) and a smartphone in the near future. The system utilizes a color pre-processing method to differentiate between the stop and go signals. A mathematical morphology algorithm is used to further enhance the traffic light detection and a circular Hough transform is utilized to detect the traffic light correctly. From the simulation results of the computer vision and image processing based on a proposed algorithm on Matlab, we found that the proposed TLD method can detect the stop and go signals from the traffic lights not only in daytime, but also at night. In the future, it will be possible to reduce the traffic accident rate by recognizing the traffic signal and informing the elderly of how to drive by voice.