• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.392-397
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• 2014

Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.1-8
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• 2017

This paper presents the development of an adaptive cruise control (ACC) system, which is one of the typical advanced driver assist systems, for 4-wheel drive hybrid in-wheel electric vehicles. The front wheels of the vehicle are driven by a combustion engine, while its rear wheels are driven by in-wheel motors. This paper proposes an adaptive cruise control system which takes advantage of the unique driveline configuration presented herein, while the proposed power distribution algorithm guarantees its tracking performance and fuel efficiency at the same time. With the proposed algorithm, the vehicle is driven only by the engine in normal situations, while the in-wheel motors are used to distribute the power to the rear wheels if the tracking performance decreases. This paper also presents the modeling of the in-wheel motors, hybrid in-wheel driveline, and integrated ACC control system based on a commercial high-precision vehicle dynamics model. The simulation results obtained with the model are presented to confirm the performance of the proposed algorithm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.261-264
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• 2006

지능형 차량정보 시스템은 21세기 교통체계로 기대를 모으고 있는 ITS(Intellligent Transport System)의 구축에 핵심이 되는 시스템이다. 이러한 시스템을 구현하기 위해서 종래의 네비게이션, 차량용 무선통신, 차량진단 등의 단일화된 시스템을 통합적으로 수행하며, 계측 또는 수집된 데이터를 분석하여 지능적으로 차량의 주행 상태를 분석 / 진단함으로써 차량에서의 안전한 운행과 운전자 및 승객들이 요구하는 정보 또는 다양한 서비스를 제공하기 위한 새로운 모듈의 개발이 절실히 필요한 실정이다. 따라서, 본 논문에서는 CAN(Controller Area Network) BUS을 이용한 차량의 상태수집 모듈과 능동 데이터베이스에 관해 기술하고 이를 통합하기 위한 임베디드 보드를 이용한 CAN BUS연계형 차량용 복합통신모듈의 프로토타입 H/W을 구성하여 실용화 가능성 및 유용성을 제시하고자 하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.1-8
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• 2013

This paper implements an integrated vehicle chassis system of ACC(Adaptive Cruise Control) and LKS(Lane Keeping System) based on OSEK OS to vehicle operating system and analyzes its performance through experiments. In recent years active safety and advanced driver assistance system has discussed to improve safety of vehicle. Among the rest, We integrate ACC that controls longitudinal velocity of vehicle and LKS that assists a vehicle in maintaing its driving lane, then implement integrated control system in vehicle. Implemented control system uses OSEK/VDX proposed standard, which is aiming at reusability and safety of software for vehicle and removal hardware dependence of application software. Redesigned control system based on OSEK OS, which is supported by OSEK/VDX, can manage real-time task, process interrupt and manage shared resource. We show by results performed EILS(ECU-In-the-Loop Simulation) that OSEK OS-based integrated controller of ACC and LKS is equivalent conventional integrated controller of ACC and LKS.

• Journal of Korean Society of Transportation
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• v.35 no.2
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• pp.116-128
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• 2017

Traffic accidents can be defined as a physical collision event of vehicles occurred instantaneously when drivers do not perceive the surrounding vehicles and roadway environments properly. Therefore, detecting the high potential events that cause traffic accidents with monitoring the interactions among the surroundings continuously by driver is the prerequisite for prevention the traffic accidents. For the analysis, basic data were collected to analyze interactions using a test vehicle which is equipped the GPS(Global Positioning System)-IMU(Inertial Measurement Unit), camera, radar and RiDAR. From the collected data, highway geometric information and the surrounding traffic situation were analyzed and then safety evaluation algorithm for driving vehicle was developed. In order to detect a dangerous event of interaction with surrounding vehicles, locations and speed data of surrounding vehicles acquired from the radar sensor were used. Using the collected data, the tangent and curve section were divided and the driving safety evaluation algorithm which is considered the highway geometric characteristic were developed. This study also proposed an algorithm that can assess the possibility of collision against surrounding vehicles considering the characteristics of geometric road structure. The methodology proposed in this study is expected to be utilized in the fields of autonomous vehicles in the future since this methodology can assess the driving safety using collectible data from vehicle's sensors.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.2
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• pp.235-240
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• 2015

Active Safety system is requested on the market of the medium and heavy duty commercial vehicle over 4.5ton beside the market of passenger car with advancement of the digital equipment proportionally. Unlike the passenger car, the mounting position of camera in case of the medium and heavy duty commercial vehicle is relatively high, it is disadvantaged conditions for lane recognition in contradiction to passenger car. In this work, we show the method of lane recognition through the Sobel edge, based on the spatial domain processing, Hough transform and color conversion correction. Also we suggest the low error method of front vehicles recognition in order to reduce the detection error through Haar-like, Adaboost, SVM and Template matching, etc., which are the object recognition methods by frontal camera vision. It is verified that the reliability over 98% on lane recognition is obtained through the vehicle test.

• Journal of IKEEE
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• v.22 no.1
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• pp.223-226
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• 2018

Recently, various safety technologies have been extensively developed to protect occupants from accidents. This paper surveys various automotive occupant protection technologies such as antilock braking system, traction control system, electronic brake distribution, electronic stability control, autonomous emergency braking, airbag, seatbelt pretensioner, and active headrest. Their operation principles and implementations are also explained.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.444-450
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• 2013

For intelligent vehicle technology, it is very important to recognize the states of around vehicles and assess the collision risk for safety driving of the vehicle. Specifically, it is very fatal the collision with the vehicle coming from opposite direction. In this paper, a centerlane violation prediction method is proposed. Only radar signal based prediction makes lots of false alarm cause of measurement noise and the false alarm can make more danger situation than the non-prediction situation. We proposed the novel prediction method using IMM algorithm and fuzzy logic to increase accuracy and get rid of false positive. Fuzzy logic adjusts the radar signal and the IMM algorithm appropriately. It is verified by the computer simulation that shows stable prediction result and fewer number of false alarm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.124-140
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• 2017

There exists a limitation to provide proper advance information for safe maneuvering through guidance and caution signs in freeway mobile work zones, unlike fixed work zones. Although a work-protection vehicle is currently deployed at the rear of the work vehicle, more active countermeasures to prevent crashes are required. The purpose of this study was to propose a method to evaluate the safety in mobile work zones and to present effective countermeasures. Driving simulation experiments were conducted to analyze characteristics of driver's behavior in mobile and fixed work zones. Safety distance index (SDI) based on the comparison of stopping distances of a work-protection vehicle and a following subject vehicle was used to evaluate traffic safety. More dangerous driving behavior was observed in the mobile work zone. Especially, it was identified that the lane-change of vehicles following the work- protection vehicle was late. Therefore, it is necessary to actively introduce methods to provide warning information so that the driver can recognize the work-protection vehicle in advance and carry out appropriate evasive maneuvers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.225-231
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• 2013

A bird's-eye view is an elevated view of an object from above, with a perspective as though the observer were a bird, often used in the making of blueprints, floor plans and maps. It can be used under severe weather conditions when visibility is poor. Under low visibility environments, drivers can communicate each other using V2V communication to get each vehicle's status to prevent collision and other accidents. Ubiquitous transportation sensor networks(u-TSN) and its application are emerging rapidly as an exciting new paradigm to provide reliable and comfortable transportatione services. The ever-growing u-TSN and its application will provide an intelligent and ubiquitous communication and network technology for traffic safety area.