• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.117-122
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• 2016

In this paper, we propose 24-GHz CMOS radio frequency (RF) power amplifier for short-range automotive collision avoidance radars. This circuit contains common source stage with inter-stages conjugate matching circuit as a class-A mode amplifier. The proposed circuit is designed using TSMC $0.13-{\mu}m$ mixed signal/RF CMOS process ($f_T/f_{MAX}=120/140GHz$). It operates at the supply voltage of 2V, and it is designed to have high power gain, low insertion loss and low noise figure in the low supply voltage. To reduce total chip area, the circuit used transmission lines instead of the bulky real inductor. The designed CMOS power amplifier showed the smallest chip size of $0.1mm^2$, the lowest power consumption of 40mW, the highest power gain of 26.5dB, the highest saturated output power of 19.2dBm and the highest maximum power-added efficiency of 17.2% as compared to recently reported results.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.6
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• pp.57-65
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• 1994

A collision-free path planning algorithm between an articulated robot and polyhedral obstacles using configuration space is presented. In configuration space, a robot is treated as a point and obstacles are treated as grown forbidden regions. Hence path planning problem is transformed into moving a point from start position to goal position without entering forbidden regions. For mapping to 3D joint space, slice projection method is used for first revolute joint and inverse kinematics is used for second and third revolute joint considering kinematic characteristics of industrial robot. Also, three projected 2D joint spaces are used in search of collision-free path. A proper example is provided to illustrate the proposed algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.5
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• pp.126-135
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• 2014

This paper describes the development and verification of control algorithms for V2X and environmental sensor integrated intersection support and safety systems. The objective of the research is to develop core technologies for effective fusion of V2X and environmental sensors and to develop new safety function for intersection safety. One of core technologies is to achieve the improvement of GPS accuracy, and the other is to develop the algorithm of a vehicle identification which matches all data from V2X, vehicle sensors and environmental sensors to specific vehicles. A intersection optimal pass (IOP) algorithm is designed based on these core technologies. IOP recommends appropriate speed to pass the intersection in the consideration of traffic light signal and preceeding vehicle existence. Another function is developed to prevent a collision avoidance when car crash caused by traffic violation of surrounding vehicles is expected. Finally all functions are implemented and tested in three test vehicles. It is shown that IOP can support convenient and comfortable driving with recommending optimal pass speed and collision avoidance algorithm can effectively prevent collision caused by traffic sign violation of surrounding vehicles.

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.493-504
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• 2007

This paper proposes a stereo vision-based forward obstacle detection and distance measurement method. In general, stereo vision-based obstacle detection methods in automotive applications can be classified into two categories: IPM (Inverse Perspective Mapping)-based and disparity histogram-based. The existing disparity histogram-based method was developed for stop-and-go applications. The proposed method extends the scope of the disparity histogram-based method to highway applications by 1) replacing the fixed rectangular ROI (Region Of Interest) with the traveling lane-based ROI, and 2) replacing the peak detection with a constant threshold with peak detection using the threshold-line and peakness evaluation. In order to increase the true positive rate while decreasing the false positive rate, multiple candidate peaks were generated and then verified by the edge feature correlation method. By testing the proposed method with images captured on the highway, it was shown that the proposed method was able to overcome problems in previous implementations while being applied successfully to highway collision warning/avoidance conditions, In addition, comparisons with laser radar showed that vision sensors with a wider FOV (Field Of View) provided faster responses to cutting-in vehicles. Finally, we integrated the proposed method into a longitudinal collision avoidance system. Experimental results showed that activated braking by risk assessment using the state of the ego-vehicle and measuring the distance to upcoming obstacles could successfully prevent collisions.

• Transactions of the Korean Society of Automotive Engineers
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• v.4 no.3
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• pp.168-175
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• 1996

Except the collision avoidance performance related to the rapid lane change, the 4WS vehicle has better dynamic stability and handling performance than the conventional 2WS vehicle which has close relation with the driver's safety, a 4WS conrol method with the effect of steering wheel angular velocity is proposed based on the fact that the driver steers abruptly the steering wheel to avoid the collision. And the effects of the proposed 4WS control method are investigated on the dynamic stability and handling performance by using the ISO lane change test code.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.319-325
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• 2011

Recently, collision avoidance systems are under development to reduce the traffic accidents and driver comfort for automotive radar. Pulse radar can detect their range and velocities of moving vehicles using range gate and FFT(Fast Fourier Transform) of the doppler frequency. We designed the real time DSP(Digital Signal Processing) based automotive UWB(Ultra Wideband) radar, and implemented DSP to detect the range and velocity within 100ms for real time system of the automotive UWB radar. We also measured the range and velocity of a moving vehicle using designed automotive UWB radar in a real road environment.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.210-216
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• 2016

This paper presents a novel collision avoidance technique for mobile robots based on omni-directional vision simultaneous localization and mapping (SLAM). This method estimates the avoidance path and speed of a robot from the location of an obstacle, which can be detected using the Lucas-Kanade Optical Flow in images obtained through fish-eye cameras mounted on the robots. The conventional methods suggest avoidance paths by constructing an arbitrary force field around the obstacle found in the complete map obtained through the SLAM. Robots can also avoid obstacles by using the speed command based on the robot modeling and curved movement path of the robot. The recent research has been improved by optimizing the algorithm for the actual robot. However, research related to a robot using omni-directional vision SLAM to acquire around information at once has been comparatively less studied. The robot with the proposed algorithm avoids obstacles according to the estimated avoidance path based on the map obtained through an omni-directional vision SLAM using a fisheye image, and returns to the original path. In particular, it avoids the obstacles with various speed and direction using acceleration components based on motion information obtained by analyzing around the obstacles. The experimental results confirm the reliability of an avoidance algorithm through comparison between position obtained by the proposed algorithm and the real position collected while avoiding the obstacles.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1740-1741
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• 2011

This paper proposes a new linear recursive target state estimator for automotive collision warning system. The target motion is modeled in Cartesian coordinate system while the radar measurements such as range, line-of-sight angle and range rate are obtained in polar coordinate system. To solve the problem by nonlinear relation between these two coordinate system, a practical linear filter design scheme employing the predicted line-of-sight Cartesian coordinate system (PLCCS) is proposed. Especially, PLCCS can effectively incorporate range rate measurements into target tracking system. It is known that the utilization of range rate measurements enables the improvement of target tracking performance. Moreover, PLCCS based target tracking system is implemented by linear recursive filter structure and hence is more suitable scheme for the development of reliable collision warning system. The performance of the proposed method is demonstrated by computer simulations.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.60-64
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• 2022

In the automotive industry, the development of automobiles to meet safety requirements is becoming increasingly complex. This is because quality evaluation agencies in each country are continually strengthening new safety standards for vehicles. Among these various requirements, collision safety must be satisfied by controlling airbags, seat belts, etc., and can be defined as post-crash safety. Apart from this safety system, the Advanced Driver Assistance Systems (ADAS) use advanced detection sensors, GPS, communication, and video equipment to detect the hazard and notify driver before the collision. However, research to improve passenger safety in case of an accident by using the sensor of active safety represented by ADAS in the existing passive safety is limited to the level that utilizes the sudden braking level of the FCA (Forward Collision-avoidance Assist) system. Therefore, this study aims to develop logic that can improve passenger protection in case of an accident by using ADAS information and driving information secured before a collision. The proposed logic was constructed based on LSTM deep learning techniques and trained using crash test data.

• Advances in robotics research
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• v.2 no.2
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• pp.161-182
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• 2018

This paper proposes a novel receding horizon control (RHC) algorithm for formation control of a swarm of unmanned surface vehicles (USVs) using particle swarm optimization (PSO). The proposed control algorithm provides the coordinated path tracking of multi-agent USVs while preventing collisions and considering external disturbances such as ocean currents. A three degrees-of-freedom kinematic model of the USV is used for the RHC with guaranteed stability and convergence by incorporating a sequential Monte Carlo (SMC)-based particle initialization. An ocean current model-based estimator is designed to compensate for the effect of ocean currents on the USVs. This method is compared with the PSO-based RHC algorithms to demonstrate the performance of the formation control and the collision avoidance in the presence of ocean currents through numerical simulations.