• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.04a
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• pp.588-595
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• 2014

In this paper, analysis of the vibration Characteristic for the Mine Detectable Test Platform is described. The test platform system is the multi-sensor mine detectable vehicle. This multi-sensor mine detectable unit is more efficient detection performance than other conventional methods. The test platform system has five subsystems, the UWB(Ultra Wide Band) sensor scanner, the MD(Metal Detector) sensor scanner, the neutron sensor scanner, and the detectable vehicle. We perform the vibration tests for the test platform and analyze the vibration characteristic, such as the max displacement, the max deformation and the max Von-Misses Stress.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.12
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• pp.927-934
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• 2014

In this paper, analysis of the vibration characteristic for the mine detectable test platform is described. The test platform system is the multi-sensor mine detectable vehicle. This multi-sensor mine detectable unit is more efficient detection performance than other conventional methods. The test platform system has five subsystems, the UWB(ultra wide band) sensor scanner, the MD(metal detector) sensor scanner, the ND(neutron detector) sensor scanner, and the detectable vehicle. We perform the vibration tests for the test platform and analyze the vibration characteristic, such as the max displacement, the max deformation and the max Von-Misses stress.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.2883-2890
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• 2000

In this study, a Hardware-In-The-Loop-Simulation(HILS) system for developing a Electric-Power-Steering(EPS) system is designed. To test a EPS by HILS system, a mathematical vehicle model with a steering system model has been constructed. This mathematical model has been constructed. This mathematical model has been downloaded to the Digital-Signal-Processor(DSP) board. To realize the lateral force acting on the front wheel in a real car. the steering wheel angle sensor and vehicle velocity have been used for input signal. The force sensor has been used for a feedback signal. The full vehicle states could by simulated by the HILS system. Consequently, the HILS system could by used to analyze control-parameters of a EPS that contributes to the maneuverability and stability of a vehicle. At the same time, the HILS system can evaluate the whole performance of the vehicle-steering system. Also the HILS system could do test could not be executed in real vehicle. The HILs system will useful for developing the control logic for the EPS system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1551-1558
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• 2014

We propose a multi-rate sensor fusion of vision and radar using Kalman filter to solve problems of asynchronized and multi-rate sampling periods in object vehicle tracking. A model based prediction of object vehicles is performed with a decentralized multi-rate Kalman filter for each sensor (vision and radar sensors.) To obtain the improvement in the performance of position prediction, different weighting is applied to each sensor's predicted object position from the multi-rate Kalman filter. The proposed method can provide estimated position of the object vehicles at every sampling time of ECU. The Mahalanobis distance is used to make correspondence among the measured and predicted objects. Through the experimental results, we validate that the post-processed fusion data give us improved tracking performance. The proposed method obtained two times improvement in the object tracking performance compared to single sensor method (camera or radar sensor) in the view point of roots mean square error.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.2
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• pp.133-139
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• 2014

Magnetic Sensors can be employed to localize the unmanned vehicle which is running a predefined path where magnets are embedded for certain spaces. Among various sensor types, sensor arrays of 1-dimensional magnetic sensor have the merit of easy elimination of external magnetic component such as terrestrial magnetism. However, interpolation should be considered in the array sensors in order to increase the precision level because there is a limit in arranging sensors in close interval. We propose the novel interpolation method which can be performed with simple computation and represents the improved accuracy by increasing the linearity of the interaction formula. Demonstration of the linearity and simulation results show the proposed method exhibits the improved accuracy compared to the conventional method.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.818-826
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• 2015

This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.3
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• pp.142-147
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• 2013

Over the past few years, intelligent tire is developed very actively for more accurate measurement of real-time tire forces generated during vehicle driving situation. Information on the force of intelligent tire could be used very usefully to chassis control systems of a vehicle. Intelligent tire is based on deformation of tire's inner surface from the waveform of a SAW, or Surface Acoustic Wave. The tire vertical force is estimated by using variance analysis of sensor signals. The estimated tire vertical force is compared with the tire vertical force generated during vehicle driving situation in real-time environment. The scope of this paper is a correlation study between the measured sensor signals and the tire vertical force generated during vehicle driving situation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.399-404
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• 2011

Overload vehicles have demoralizing influence upon the social overhead capital, economics of nation, traffic flow and road safe as various components. Accordingly, this study established a ubiquitous sensor network system to develop an intelligent regulation system to monitor overloaded vehicles in motion. and Unlike WIM, after detecting the axle of driving vehicles by measuring deformation of roads, this system calculates the weights of vehicles by using signals from the strain sensors installed under the road and an analysis method. Also the study conducted an simulation test for vehicle load analysis using genetic algorithm. and tested wireless sensor for USN system.

• Journal of Sensor Science and Technology
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• v.18 no.5
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• pp.385-392
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• 2009

This paper describes the algorithm development of a new body pressure detection sensor for occupant classification system. U.S. Government has required that advanced airbag system should be installed to every automobiles after 2006 according to FMVSS 208 regulation. Therefore, Occupant Classification System should be provided the passenger with safety in order to protect the infants or children that sit in the front passenger seat. When an occupant sits on the chair of the vehicle, deployment of the airbag depends on passenger's weigh distribution and postures. Authors have been developed a new pattern recognition of passenger and weight distribution at the same time by Force Sensing Resistor for the safety.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.