• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.953-955
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• 2014

최근 차량 충돌 방지를 위한 다양한 기술이 상용화되고 있다. FMCW 기반의 레이더 시스템은 구현의 용이성으로 많은 상용차에서 전면 충돌 방지 시스템에 적용되고 있다. 측면 충돌 방지를 위한 BSD(Blind Spot Detection)와 차선변경 보조 시스템(LCA, Lane Change Assistant system)에서는 전방 레이더보다 인식거리가 줄어들고 갱신율이 낮아지므로 고속 FFT 등을 수행하는 신호처리부를 저가격으로 설계가 가능할 것이다. 본 연구에서는 TI사의 MCU인 F28335를 사용하여 근거리를 인식하는 신호처리부를 설계하였다. 이 MCU는 16채널 12bit ADC와 68KB RAM 및 512KB 플래시 메모리를 내장하고, 150MHz 부동소수점 연산을 지원하여 단일 칩으로 신호처리부의 구현이 가능하다. 구현된 시스템은 20m내외의 거리에 있는 장애물에 대하여 10Hz로 갱신이 가능하여 BSD를 위한 기본 기능이 확인되었다. 이러한 구현은 이전의 고가의 DSP나 FPGA를 사용하지 않고 15$이내의 단일 MCU와 간단한 아날로그 회로로 설계되어 저가격의 시스템으로 상용화가 가능할 것이다.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.9-18
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• 2017

Ubiquitous computing is a novel paradigm that is rapidly gaining in the scenario of wireless communications and telecommunications for realizing smart world. As rapid development of sensor technology, smart sensor system becomes more popular in automobile or vehicle. In this study, a new vehicle detection mechanism in real-time for blind spot area is proposed based on imaging sensors. To determine the position of other vehicles on the road is important for operation of driver assistance systems (DASs) to increase driving safety. As the result, blind spot detection of vehicles is addressed using an automobile detection algorithm for blind spots. The proposed vehicle verification utilizes the height and angle of a rear-looking vehicle mounted camera. Candidate vehicle information is extracted using adaptive shadow detection based on brightness values of an image of a vehicle area. The vehicle is verified using a training set with Haar-like features of candidate vehicles. Using these processes, moving vehicles can be detected in blind spots. The detection ratio of true vehicles was 91.1% in blind spots based on various experimental results.

• Journal of Auto-vehicle Safety Association
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• v.4 no.1
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• pp.27-32
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• 2012

Recently, in order to reduce traffic accident related fatalities, increasing number of studies are conducted regarding the vehicle safety enhancement devices. But very few studies about test procedures and requirements for vehicle safety systems are being carried out. Since BSD, as one of the most important safety features, is installed on a new vehicle, its performance test method has to be evaluated. Independent factors irrelevant to the device types including collision position, vehicle speed and closing speed are used to calculate test distance away from the current vehicle. Effect of roadway geometry as radius of curvature is introduced to propose possible misjudgement of following vehicle as adjacent one. The study results would be utilized to enhance the test procedure of BSD performance.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.44-49
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• 2013

This paper presents a lateral collision risk index between an ego vehicle and a rear-side vehicle. The lateral collision risk is designed to represent a lateral collision risk and provide the appropriate threshold value of activation of the lateral collision management system such as the Blind Spot Detection(BSD). The lateral collision risk index is designed using the Time to Line Crossing(TLC) and the longitudinal collision index at the predicted TLC. TLC and the longitudinal collision index are calculated with the signals from the exterior sensor such as the radar equipped on the rear-side of a vehicle and a vision sensor which detects the distance and time to the lane departure. For the robust situation assessment, the perception of driving environment determining whether the road is straighten or curved should be determined. The relative motion estimation method has been proposed with the road information via the integrated estimator using the environment sensors and vehicle sensor. A lateral collision risk index was composed with the estimated relative motion considering the relative yaw angle. The performance of the proposed lateral collision risk index is investigated via computer simulations conducted using the vehicle dynamics software CARSIM and Matlab/Simulink.

• Journal of Auto-vehicle Safety Association
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• v.9 no.2
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• pp.6-12
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• 2017

An autonomous driving system based on a precise digital map is developed. The system is implemented to the Hyundai's Tucsan fuel cell car, which has a camera, smart cruise control (SCC) and Blind spot detection (BSD) radars, 4-Layer LiDARs, and a standard GPS module. The precise digital map has various information such as lanes, speed bumps, crosswalks and land marks, etc. They can be distinguished as lane-level. The system fuses sensed data around the vehicle for localization and estimates the vehicle's location in the precise map. Objects around the vehicle are detected by the sensor fusion system. Collision threat assessment is performed by detecting dangerous vehicles on the precise map. When an obstacle is on the driving path, the system estimates time to collision and slow down the speed. The vehicle has driven autonomously in the Hyundai-Kia Namyang Research Center.