• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1565-1571
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• 2010

FMCW(Frequency Modulation Continuous Wave) Radar is very useful for vehicle collision warning system because of the simplicity. In this work, a signal processing part of FMCW vehicle radar system is implemented with flexibility using DSP, FPGA, ADC, and DAC so that the system could adopt lots of algorithm and could be improved through road test. It is shown that the system meets basic requirements as designed, and finds some problems in road test. We briefly discuss the problem which are caused by shadow effect from overlapped target and the distortion of beat frequency from the nonlinearity of VCO and the RCS of vehicle.

• Journal of Auto-vehicle Safety Association
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• v.6 no.1
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• pp.27-32
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• 2014

A study assessing driver acceptance level for various active safety systems against Korean drivers has been conducted. A 2013 Cadillac ATS model vehicle was tested along southern outskirt of Seoul including local roadway and interurban highway. Active safety systems included were FCA(Forward Collision Alert), LDW(Lane Departure Warning), SBZA(Side Blind Zone Alert), FRPA(Front/Rear Park Assist), RCTA(Rear Cross Traffic Alert), ACC(Adaptive Cruise Control), and AEB(Autonomous Emergency Braking). Participants experienced the FRPA, RCTA and AEB features in a controlled parking lot with a dummy vehicle and traffic cones as target obstacles. Remaining features have been tested on the accumulated stretched of 106 km long urban and interurban roadway. Series of questionnaires corresponding to each active safety systems have been conducted. Tentative results revealed that RCTA and SBZA systems received favourable ratings compared to the other ones.

• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.102-106
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• 2012

The purpose of this paper is to study the failure cases in relation to system of Air Bag in vehicle happened in the field. In the first example, it was separated the soldering parts connected the wire pin between air bag module and clock spring of air bag. Whenever the pin shake by the car's vibration, the driver verified the malfunction phenomenon appeared air bag warning lamp on instrument panel in front of driver's seat. in car inside room. The second example, it verified the warning lamp lighting phenomenon of air bag by produced the circuit plate non-contacting of single an element in air bag electronic control unit. The third example, it verified the light of air bag warning indicator lamp by separated with soldering parts connecting inner pin and resistance terminal of seat belt pretensioner using passenger seat. The fourth example, when the passenger car crash a back of truck, the former bumper get jammed under the latter as the roof height of car low less than that. Therefore, the impact of Car's collision verified that don't transfer with body frame of vehicle because of no attachment impact sensor in it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.815-818
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• 2016

Forward collision warning systems(FCWS) and lane departure warning systems(LDWS) need regions of interest for detecting lanes and objects as road regions. In general, the lane departure warning system using a vehicle front camera is tracking a lane curve using RANSAC or the like in the form of a straight line obtained image are compared with the center of the vehicle. This algorithm has weaknesses that requires a wide range of the lane being vulnerable to the curve. This paper presents an algorithm that checks whether the current lane departure by car from the Top-view space. The algorithm also can check whether the vehicle in the lane departure of the narrow range, and shows the result that is almost not affected by noise.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.17-23
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• 2013

This paper describes an algorithm for Advanced Emergency Braking(AEB) with tire-road friction coefficient estimation. The AEB is a system to avoid a collision or mitigate a collision impact by decelerating the car automatically when forward collision is imminent. Typical AEB system is operated by Time-to-collision(TTC), which considers only relative velocity and clearance from control vehicle to preceding vehicle. AEB operation by TTC has a limit that tire-road friction coefficient is not considered. In this paper, Tire-road friction coefficient is also considered to achieve more safe operation of AEB. Interacting Multiple Model method(IMM) is used for Tire-road friction coefficient estimation. The AEB algorithm consists of friction coefficient estimator and upper level controller and lower level controller. The numerical simulation has been conducted to demonstrate the control performance of the proposed AEB algorithm. The simulation study has been conducted with a closed-loop driver-controller-vehicle system using using MATLAB-Simulink software and CarSim Vehicle model.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.56-61
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• 2013

This paper presents a development of the Advanced Emergency Braking (AEB) Algorithm for passenger vehicles. The AEB is the system to slow the vehicle and mitigate the severity of an impact when a rear end collision probability is increased. To mitigate a rear end collision, the AEB comprises of a millimeter wave radar sensor, CCD camera and vehicle parameters of which are processed to judge the likelihood of a collision occurring. The main controller of the AEB algorithm is composed of the two control stage: upper and lower level controller. By using the collected obstacle information, the upper level controller of the main controller decides the control mode based not only on parametric division, but also on physical collision capability. The lower level controller determines warning level and braking level to maintain the longitudinal safety. To decide the braking level, Last Ponit To Brake and Steer (LPTB/LPTS) are compared with current driving statues. To demonstrate the control performance of the proposed AEBS algorithm's, closed-loop simulation of the AEBS was conducted by using the Matlab simlink and CarSim software.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.126-141
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• 2019

One of the Cooperative Intelligent Transportation System(C-ITS) priority services is collision prevention support service. Several studies have considered V2I2V communication-based collision prevention support services using Artificial Neural Networks(ANN). However, such services still show some issues due to a low penetration of C-ITS devices and large delay, particularly when loading massive traffic data into the server in the C-ITS center. This study proposes the Artificial Neural Network-based Collision Warning Service(ACWS), which allows upstream vehicle to update pre-determined weights involved in the ANN by using real-time sectional traffic information. This research evaluates the proposed service with respect to various penetration rates and delays. The evaluation result shows the performance of the ACWS increases as the penetration rate of the C-ITS devices in the vehicles increases or the delay decreases. Furthermore, it reveals a better performance is observed in more advanced ANN model-based ACWS for any given set of conditions.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.96-108
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• 2017

The current collision warning and avoidance system(CWAS) is one of the representative Advanced Driver Assistance Systems (ADAS) that significantly contributes to improve the safety performance of a vehicle and mitigate the severity of an accident. However, current CWAS mainly have focused on preventing a forward collision in an uninterrupted flow, and the prevention performance near intersections and other various types of accident scenarios are not extensively studied. In this paper, the safety performance of Vision-Sensor (VS) and Radar-Sensor(RS) - based collision warning systems are evaluated near an intersection area with the data from Naturalistic Driving Study(NDS) of Second Strategic Highway Research Program(SHRP2). Based on the VS and RS data, we newly derived sixteen vehicle-to-vehicle accident scenarios near an intersection. Then, we evaluated the detection performance of VS and RS within the derived scenarios. The results showed that VS and RS can prevent an accident in limited situations due to their restrained field-of-view. With an accident prevention rate of 0.7, VS and RS can prevent an accident in five and four scenarios, respectively. For an efficient accident prevention, a different system that can detect vehicles'movement with longer range than VS and RS is required as well as an algorithm that can predict the future movement of other vehicles. In order to further improve the safety performance of CWAS near intersection areas, a communication-based collision warning system such as integration algorithm of data from infrastructure and in-vehicle sensor shall be developed.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.149-156
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• 2005

In this paper, the VR(Virtual Reality) simulation system is developed to analyze driver's perceptive response on the ASV(Advanced Safety Vehicle). The ASV is the vehicle of next generation equipped with various warning systems. For the purpose, the VR simulation system consists of VR database, vehicle dynamic model, graphic/sound system, and driving system. The VR database which generates 3D graphic and sound information is organized for the driving reality. Mathematical models of vehicle dynamic analysis are constructed to represent the dynamic behavior of a vehicle. The driving system and the graphic/sound system provide a driver with the operation of a vehicle and the feedback of a driving situation. Also, the real-time simulation algorithm synchronizes the vehicle dynamic model with the VR database. To check the validity of the developed system, a simple scenario is applied to investigate driver's perceptive response time and vehicle acceleration on an emergency situation. It is confirmed that the proposed system is useful and helpful to design the FVCWS(Forward Vehicle Collision Warning System).