• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.138-144
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• 2020

Currently, an autonomous vehicle studies are working to develop a four-level autonomous vehicle that can cope with emergencies. In order to flexibly respond to an emergency, the autonomous vehicle must move in a direction to minimize the damage, which must be conducted by judging all the states of the road, such as the surrounding pedestrians, road conditions, and surrounding vehicle conditions. Therefore, in this paper, we suggest a passenger detection and sharing system to detect the passenger situation inside the autonomous vehicle and share it with V2V to the surrounding vehicles to assist in the operation of the autonomous vehicle. Passenger detection and sharing system improve the weighting method that recognizes passengers in the current vehicle to identify the passenger's position accurately inside the vehicle, and shares the passenger's position of each vehicle with other vehicles around it in case of emergency. So, it can help determine the driving of a vehicle. As a result of the experiment, the body pressure sensor applied to the passenger recognition sub-module showed about 8% higher accuracy than the conventional resonant sensor and about 17% higher than the piezoelectric sensor.

• Journal of Advanced Navigation Technology
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• v.21 no.3
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• pp.251-257
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• 2017

Recently, hybrid positioning system combining GPS, vision sensor, and inertial sensor has drawn many attentions to estimate accurate vehicle positions. Since accurate multi-sensor fusion requires efficient time synchronization, this paper proposes an efficient method to obtain time synchronized measurements of vision sensor, inertial sensor, and OBD device based on GPS time information. In the proposed method, the time and position information is obtained by the GPS receiver, the attitude information is obtained by the inertial sensor, and the speed information is obtained by the OBD device. The obtained time, position, speed, and attitude information is converted to the color information. The color information is inserted to several corner pixels of the corresponding image frame. An experiment was performed with real measurements to evaluate the feasibility of the proposed method.

• Journal of IKEEE
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• v.24 no.1
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• pp.232-237
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• 2020

In this paper, we propose an efficient sensor fusion method for autonomous vehicle recognition and distance measurement. Typical sensors used in autonomous vehicles are radar, lidar and camera. Among these, the lidar sensor is used to create a map around the vehicle. This has the disadvantage, however, of poor performance in weather conditions and the high cost of the sensor. In this paper, to compensate for these shortcomings, the distance is measured with a radar sensor that is relatively inexpensive and free of snow, rain and fog. The camera sensor with excellent object recognition rate is fused to measure object distance. The converged video is transmitted to a smartphone in real time through an IP server and can be used for an autonomous driving assistance system that determines the current vehicle situation from inside and outside.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.217-228
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• 2024

LiDAR(Light Detection And Ranging) sensors, which play a pivotal role among cameras, RADAR(RAdio Detection And Ranging), and ultrasonic sensors for the safe operation of autonomous vehicles, can recognize and detect objects in 360 degrees. However, since LiDAR sensors use lasers to measure distance, they are vulnerable to attackers and face various security threats. In this paper, we examine several security threats against LiDAR sensors: relay, spoofing, and replay attacks, analyze the possibility and impact of physical jamming attacks, and analyze the risk these attacks pose to the reliability of autonomous driving systems. Through experiments, we show that jamming attacks can cause errors in the ranging ability of LiDAR sensors. With vehicle-to-vehicle (V2V) communication, multi-sensor fusion under development and LiDAR anomaly data detection, this work aims to provide a basic direction for countermeasures against these threats enhancing the security of autonomous vehicles, and verify the practical applicability and effectiveness of the proposed countermeasures in future research.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2009.05a
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• pp.190-195
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• 2009

자동차 이용자 수가 증가 할수록 자동차 사고로 인한 피해도 많이 늘어나고 있다. 이러한 자동차 사고를 사전에 예방하기 위해서는 운전자의 상태 및 현재 차량 상태를 파악하여 사고를 미리 방지함으로서 운전자의 안전을 보조할 수 있는 시스템이 필요하다. 본 연구에서는 안전운전을 보조하기 위하여 졸음운전 여부 감지 시스템, 후진시 후방 안전거리를 감지하는 시스템, 쾌적한 운전 환경을 위한 실내 환경 측정 시스템, 주차 시 생길 수 있는 사고에 대한 감시시스템을 센서와 MCU등을 이용한 임베디드 시스템을 구현 하였다.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.289-291
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• 2012

수중 센서 네트워크에서는 물 속 이라는 환경적 특성으로 인해 네트워크 구성에 있어서 많은 어려움이 있다. 특히 에너지면 측면에서 지속적으로 공급받거나 충전시킬 수 없기 때문에 전체 센서 네트워크 연결을 방해하는 요소로 작용하게 되며, 효율적인 데이터 관리도 어렵다. 이러한 문제를 해결 할 수 있는 적합한 방법이 클러스터링이다. 따라서 본 논문에서는 수중이동 차량 그룹의 환경에 적합한 효율적인 클러스터링 프로토콜을 보인다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.121-130
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• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.109-120
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• 2017

It is important to estimate objectively in the driving test. Especially, the driving test is examined by totally driving ability, rule observation and situational judgement. For this, a grading automation system for driving test was presented by using GPS, sensor data and equipment operation informations. This system is composed of vehicle mounted module, automatic grading terminal, data controller, data storage and processing server. The vehicle mounted module gathters sensor data in the car. The terminal performs automatic grading using the received sensor data according the driving test criterion. To overcome the misposition of vehicle in the map due to GPS error, we proposed the automatic grading system by map matching method, path deviation and return algorithm. In the experimental results, it was possible to grade automatically, display the right position of the car, and return to the right path under 10 seconds when the vehicle was out of the shadow region of the GPS. This system can be also applied to the driving education.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.247-252
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• 2014

Traffic network is composed of passing vehicls, delayed vehicles, traffic situation which is traffic incomes of traffic interfacing system. Traffic green time light is concluded by inside input factor, that is green light cycle, yellow light cycle, led light cycle, which light cycle is sensor inputs. That light cycle is converted to traffic phase composed of passing peoples and delayed vehicles, whose intervals is concluding of traffic network factors composed of consumptiom power factors, delayed time situation, occupying sensor nodes. This is very important sector,because of much poor traffic situation.

• Electronics and Telecommunications Trends
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• v.22 no.3 s.105
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• pp.1-11
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• 2007

USN 기반 텔레매틱스 서비스는 텔레매틱스 시장의 성숙, 유비쿼터스 사회에 대한 열망 및 u-City 사업의 가속화 등에 기인하여, 도로 교통 인프라에 USN 기술을 적용함으로써 대두하게 된 새로운 개념의 서비스이다. 본 고에서는 USN 기반 텔레매틱스 서비스 및 시장 동향, 해외사례, 관련 특허 및 국내기술개발 동향을 살펴보고자 한다. 현재 중점을 두는 구체적인 서비스는 도로 및 교차로 환경에서의 상황정보 제공 서비스로 도로 위에 설치된 T-센서노드를 이용하여 시간 및 방향에 따라 진입하는 차량의 실시간 위치, 속도, 시간 정보를 수집한 뒤 센서 네트워크를 통해 T-베이스스테이션으로 관련 정보를 전달하고 차량 충돌이라는 교통사고를 미연에 방지하기 위한 상황인지적 서비스를 제공하는 것이다. 이를 위한 핵심 기술로 T-센서노드 기술, 센서노드 네트워크 기술 및 T-베이스스테이션 기술이 있으며 중점적으로 개발하고 있다.