• 한국정보통신학회논문지
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• 제14권7호
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• pp.1565-1571
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• 2010

FMCW(Frequency Modulation Continuous Wave) 레이더는 간단하게 장애물의 거리와 속도를 검출할 수 있어 차량용 충돌 방지 시스템에 많이 사용된다. 본 연구에서 개발된 FMCW 차량 레이더 시스템의 신호처리 부는 DSP, FPGA, 고속 ADC 및 DAC 등을 활용한 유연한 구조로 설계 되어 다양한 알고리즘에 대하여 개선 방안을 적용, 평가할 수 있도록 설계되었다. 구현된 시스템은 기본 동작 성능이 설계 성능과 유사함을 확인하였으며, 실제 주행시험을 통하여 상용화에 필요한 몇가지 문제점을 분석하고 이에 대한 개선 방안을 제시하였다. 제기된 문제점을 분석하여 타겟들의 겹침으로 인한 새도우 효과(Shadow effect), VCO의 비선형 특성에 따른 비트주파수의 퍼짐, 차량 형상에 따른 비트주파수의 군집화로 구분하였으며 이에 대한 해결방안을 간단히 살펴보았다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.262-266
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• 2014

Military vehicle equipped with an antenna and a shelter for operating radar has a vibration exposure during driving time. This vibration would have influence on structure of military vehicle critically. In this paper, driving stability of the military vehicle is obtained through the vibration response analysis. And, vibration level of the military vehicle satisfied the military vibration specification through analysis and comparing the MIL-STD-810G. PSD and Grms data obtained by road test can be used for vibration test specification of cabinets and electronic equipment in shelter.

• 정보저장시스템학회논문집
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• 제11권2호
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• pp.26-30
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• 2015

Recently, military vehicles are driven with a lot of electronic devices such as radar, antenna, and information storage devices. However, the military vehicles can be exposed to impact easily. Therefore, they have to be designed robustly in order to ensure the stability of the vehicle and the electronic devices. To achieve that, the dynamic behaviors of the military vehicle should be exactly identified. Therefore, in this research, dynamic behaviors of the vehicles were identified by carrying out road tests and we constructed finite element model to analyze the dynamic characteristics of the vehicle.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1505-1515
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• 2016

The age of autonomous vehicles has come according to development of high performance sensing and artificial intelligence technologies. And importance of the vehicle's surrounding environment sensing and observation is increasing accordingly because of its stability and control efficiency. In this paper we propose an integrated platform for efficient networking, analysis and monitoring of multiple sensing data on the vehicle that are equiped with various automotive sensors such as GPS, weather radar, automotive radar, temperature and humidity sensors. From simulation results, we could see that the proposed platform could perform realtime analysis and monitoring of various sensing data that were observed from the vehicle sensors. And we expect that our system can support drivers or autonomous vehicles to recognize optimally various sudden or danger driving environments on the road.

• 한국ITS학회 논문지
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• 제14권1호
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• pp.1-12
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• 2015

매설형 검지기는 검지 성능이 타 검지기에 비해 우수하지만, 설치 및 관리비용이 클 뿐 아니라 도로의 재포장이나 도로파손으로 인해 수명이 짧다는 단점이 있다. 이에 반해 기존 지주에 부착하여 사용하는 검지시스템인 비매설형검지기는 도로 노면을 손상시키지 않기 때문에 설치가 쉽고, 유지관리비용이 적다는 장점이 있다. 비매설식 검지기는 이러한 장점에도 불구하고, 검지 성능이 낮아 아직까지 신호제어용으로 사용하지 못하는 실정이다. 본 연구에서는 비매설형검지기 중에 정확도가 가장 높은 FMCW 방식의 레이더에 대해 성능평가를 수행하고, 신호제어용 검지용도별로 현장적용 유/무 결과를 제시하였다.

• 제어로봇시스템학회논문지
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• 제21권2호
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• pp.121-129
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• 2015

This paper presents a multiple vehicle recognition algorithm based on radar and vision sensor fusion for lane change assistance. To determine whether the lane change is possible, it is necessary to recognize not only a primary vehicle which is located in-lane, but also other adjacent vehicles in the left and/or right lanes. With the given sensor configuration, two challenging problems are considered. One is that the guardrail detected by the front radar might be recognized as a left or right vehicle due to its genetic characteristics. This problem can be solved by a guardrail recognition algorithm based on motion and shape attributes. The other problem is that the recognition of rear vehicles in the left or right lanes might be wrong, especially on curved roads due to the low accuracy of the lateral position measured by rear radars, as well as due to a lack of knowledge of road curvature in the backward direction. In order to solve this problem, it is proposed that the road curvature measured by the front vision sensor is used to derive the road curvature toward the rear direction. Finally, the proposed algorithm for multiple vehicle recognition is validated via field test data on real roads.

• 한국자동차공학회논문집
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• 제7권5호
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• pp.258-267
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• 1999

An intelligent safety vehicle(ISV) should have an ability to predict the possibility of an accident and help a driver avoid the accident in advance. The basic function of the ISV is to alert the driver by warning when the collision is to occur. For this purpose, the ISV has to function efficiently in sensing the environmental context. While image processing provides lane information, laser radar senses road obstacles including vehicles. By applying a simple clustering algorithm to radar signals, it is possible to obtain the vehicle information. Consequently, we can identify the existence of the vehicle of interest on my lane. The reliability of the sensing algorithm is evaluated by running on the highway with a test vehicle.

• 자동차안전학회지
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• 제10권1호
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• pp.38-44
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• 2018

This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.

• 한국정밀공학회지
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• 제33권10호
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• pp.797-804
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• 2016

The vehicle-mounted radar system (VMRS) including its electronic parts must be designed so that its performance is maintained under varying environmental conditions. The important aspects are typically weight and safety. Since many rotating VMRSs have been developed, discussion about the vibration and shock requirements for the transportation conditions has occurred: in addition, the dynamic unpaved, paved, and off-road effects have been emphasized with respect to lightweight designs. A lightweight-design VMRS should be capable of operating stably under the wind condition with the support of the vehicle structure. In this paper, a structural analysis regarding the support of the VMRS is performed, whereby the real-load conditions for three types of road and pressure were employed in terms of the wind condition. The structural analysis for the safety of the VMRS is performed, and the structural-integrity analytical processes of the VMRS are presented for different load conditions.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.190-201
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• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.