• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.5
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• pp.222-227
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• 1998

Collision warning systems have been an active research and development area as the interests and demands for ASV's (Advanced Safety Vehicles) have increased. This paper presents an experimental investigation of a collision warning system for automobiles. A collision warning HiLS(Hardware-in-the-Loop Simulation) system has been designed and used to test the collision warning algorithm, radar sensors, and warning displays under realistic operating conditions in the laboratory. the collision warning algorithm is operated by a warning index, which is a function of the warning distance and the braking distance. The computer calculates velocities of the preceding vehicle and following vehicle, relative distance and relative velocity of the vehicles using vehicle simulation models. The relative distance and the relative velocity are applied to the vehicle simulator controlled by a DC motor.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.8
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• pp.233-247
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• 1999

Traffic accidents are normally caused by late or faulty judgements due to the driver's inaccurate estimation of the distance, velocity, and acceleration from the surrounding vehicles as well as his carelessness or inattention. Thus, the development of collision avoidance systems is motivated by their great potential for increased vehicle safety. A typical collision avoidance system consists of the forward-looking sensor, the criteria for activation of collision warming and avoidance, the collision avoidance maneuvers, and the user interface. This thesis is concerned with the development of a collision warning algorithm in which the driver is warned of approaching collision with the visual and/or the audible signals . The warning algorithm based on fuzzy logic is presented here based on new warning criteria. It has been newly derived from the conventional warning equation by adding a new input variable of the required deceleration to avoid collision. The algorithm is also able to adapt to the individual driver's taste along with the different road conditions by externally controlling the warning intensity. Finally , the proposed algorithm has been validated using computer simulation.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.647-652
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• 2000

This paper proposes a collision warning/avoidance algorithm using a trajectory prediction method. This algorithm is based on 2-dimensional kinematics and the Kalman filter has been used to obtain the information of the object vehicle. This algorithm has been investigated via computer simulation and showed a good trajectory prediction performance. The proposed collision warning/avoidance algorithm would enhanced driver acceptance for a collision warning/avoidance system.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.5-10
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• 2013

This paper describes a Forward Collision Warning (FCW) system based on the radar driven fusion with camera. The objective of FCW system is to provide an appropriate alert with satisfying the evaluation scenarios of US-NCAP and a driver acceptance. For this purpose, this paper proposed a data fusion algorithm and a collision warning algorithm. The data fusion algorithm generates information of fusion target depending on the confidence of camera sensor. The collision warning algorithm calculates indexes and determines an appropriate alert-timing by using analysis results of manual driving data. The FCW system with the proposed data fusion and collision warning algorithm was investigated via scenarios of US-NCAP and a real-road driving. It is shown that the proposed FCW system can improve the accuracy of an alarm-timing and reduce the false alarm in real roads.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.2
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• pp.213-221
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• 2009

An aircraft collision accident is a disaster that causes great losses of inventories and lives. Though a collision avoidance warning function is provided automatically to pilots in the aircrafts by the enhancement of the aircraft capability, achieving fast decision-making to escape a collision situation is a complex and dangerous work for pilots. If an in-flight collision situation is controlled by the air traffic control system which monitors all airplanes in the air, it would be more efficient to prevent in-flight collisions because it can handle the emergency before the pilot's action. In this paper, we develop the collision avoidance warning function in the air traffic control system. Specifically, we design and implement the five stages of the collision avoidance function, and propose a visualization method which could effectively provide the operators with the trajectories and altitudes of the aircrafts in a collision situation. By developing an in-flight collision warning function in the air traffic control system that visualizes flight patterns through the state transition data of in-flight aircrafts on the flight path lines, it can effectively prevent in-flight collisions with traffic alerts. The developed function allows operators to effectively select and control the aircraft in a collision situation by providing the operators with the expected collision time, the relative distance, and the relative altitude while assessing the level of alert, and visualizing the alert information which includes the Attention-Warning-Alert phase via embodying the TCAS standard. With the developed function the air traffic control system could sense an in-flight collision situation before the pilot's decision-making moment.

• 한국ITS학회:학술대회논문집
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• 2004.11a
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• pp.294-299
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• 2004

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.656-659
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• 1997

In order to improve vehicle safety, collision warning systems have been proposed by many researchers. This paper presents several algorithms to determine the degree of real end collision by using fuzzy logic and neural networks. In order to provide realistic data for the algorithm design, a data collection system has been installed on a passenger car.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.157-167
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• 2011

Although vehicles become more intelligent for convenience and safety of drivers, traffic accidents are increased more and more. Especially, car-to-car single rear impacts in the urban area are increased rapidly because of driver inattention. To prevent rear impacts in the urban area, commercial automobile vendor applies the low-speed short-distance collision warning system. This paper presents low-speed short-distance collision warning algorithm for the city driving by using sensor fusion of laser sensor and ultrasonic sensor. An experiment using embedded microprocessor in the driving track was used to demonstrate the feasibility of the collision warning algorithm.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.295-300
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• 2012

Various forward collision warning algorithms have studied in order to protect a car accident. For this, in general, algorithms using an external device such as a camera and sensor generate a forward collision warning. However, if using the external device, it can occur errors due to device characteristics when there is rain or fog. Also, the prevention of a chain-reaction collision is insufficient because the system generates a warning in case of only vehicle having a forward collision danger. If it combines the vehicle safety communications, the method becomes a solution to protect a chain-reaction collision. So, In this paper, we proposes a improved forward collision warning algorithm using the wireless communication technique, driver's information, breaking distance, and velocity. And we compare and analyze our algorithm and previous algorithms.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.939-943
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• 2004

The side and rear-side collision warning system using fuzzy control algorithms is discussed in this paper. Common rearside warning system has many problems. For example if target vehicle comes into the warning area, it must unconditionally warn. Drivers could be interrupted by it. To solve the problem, I divided measuring area into two sections. One section is blind area of vehicle and the other rear-side area. For blind area, obtained data was filtered inefficient warning signal by using relative velocity method. For rear-side area, a fuzzy logic algorithm is used to recognition of obstacles. According to our experiment relative velocity method and fuzzy logic algorithms were very efficient.