• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.132-140
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• 2002

A momentum backpropagation neural network is prepared to carry out real-time dynamics simulations of a passenger car. A full-car model of fifteen degrees of freedom was constructed for vehicle dynamics analysis. Human body dynamics analysis was performed for a male driver(50 percentile Korean adult) restrained by a three point seatbelt system. The trained data using the neural network were obtained using a dynamic solver, ADAMS . The neural network were formed based on the dynamics of the simulator. The optimized hidden layer was obtained by selecting the optimal number of hidden layers. The driving scenario including bump passing and lane changing has been used for the estimation of the proposed neural network. A comparison between the trained data and neural network outputs is found to be satisfactory to show the applicability of the suggested approach.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.119-128
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• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.48-57
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• 1997

A computer aided analysis and design system is developed for analyzing the driveline torsional vibration of a vehicle. Torsional vibration characteristics of driveline component are investigated and 10 types of module are developed. They can be connected together to represent any driveline configuration. During assembly process simulation program is generated. It is implemented using C++language. A driveline tor- sional vibration system at full load driving condition and idle rattle system are modeled and simulated with this system. Their responses for engine torque excitation are evaluated on time and frequency domain, and the results are compared with test results favorably. This system makes it simpler and easier for design and analysis engineer to model and analyse the driveline system.

• KIEE International Transactions on Electrophysics and Applications
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• v.5C no.1
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• pp.14-17
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• 2005

In this paper, an automated methodology for generating model parameters considering real manufacturing processes is presented with verified results. In addition, the outcomes of applications to the next generation of flash memory devices using the parameters calibrated from the process specification decision are analyzed. The test vehicle is replaced with a well-calibrated TCAD simulation. First, the calibration methodology is introduced and tested for a flash memory device. The calibration errors are less than 5% of a full chip operation, which is acceptable to designers. The results of the calibration are then used to predict the I-V curves and the model parameters of various transistors for the design of flash devices.

• International Journal of Naval Architecture and Ocean Engineering
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• v.2 no.2
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• pp.57-67
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• 2010

Experimental investigations were carried out on an Axi-symmetric Body Model fitted with Pump-jet Propulsor (PJP) in the Cavitation Tunnel at Naval Science and Technological Laboratory (NSTL). The tests were intended for evaluating the propulsion characteristics of the body and propulsor. The self propulsion point of the model for two configurations was determined after finding the corrections for tunnel blockage effects and differences in model length at zero trim. The results were found to match closely with the towing tank results. The rotor and stator torques also matched closely over full range of experiment. Further experiments were carried out on the body at $4.5^{\circ}$ angle of trim to investigate the propulsive performance and assess the operational difficulties in the sea. The results indicated an increase in resistance and decrease in rotor thrust; but the balance of torques between the rotor and stator was undisturbed, causing no concern to vehicle roll.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.431-437
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• 2017

In this study, based on the RPS algorithm, the application results to an electrically controlled suspension system using previewed road information are presented. Reducing the excessive vibration induced by a disturbance transmitted to the system and secure its stability is a major issue. In particular, in the automotive industry, the demand is constantly being raised. A typical external disturbance causing vibration and instability of a vehicle is an irregular roadway surface that contacts a running vehicle tire. Therefore, obtaining such profile information is an important process. The RPS algorithm using a multi sensor system was constructed and implemented in a real car. Through experimental work using the RPS system included non-contact type optical sensors, it could robustly reconstruct the road input profiles from the intermixed data onto the vehicle's dynamic motion while traveling at an uneven roadway surface. A controller with a preview control was designed in the framework of a semi-active suspension system based on the 7 degrees of freedom full vehicle model. The control performance of the system was evaluated through simulations and the results were compared with the passive vehicle condition. These results highlight the feasibility of the presented control frame.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.469-472
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• 2022

With the recent development of intelligent transportation systems, various technologies applying deep learning technology are being used. To crackdown on illegal vehicles and criminal vehicles driving on the road, a vehicle type classification system capable of accurately determining the type of vehicle is required. This study proposes a vehicle type classification system optimized for mobile traffic control systems using YOLO(You Only Look Once). The system uses a one-stage object detection algorithm YOLOv5 to detect vehicles into six classes: passenger cars, subcompact, compact, and midsize vans, full-size vans, trucks, motorcycles, special vehicles, and construction machinery. About 5,000 pieces of domestic vehicle image data built by the Korea Institute of Science and Technology for the development of artificial intelligence technology were used as learning data. It proposes a lane designation control system that applies a vehicle type classification algorithm capable of recognizing both front and side angles with one camera.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.811-815
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• 2005

Traditional passive suspension has limitations to meet the required specifications of high level trains, and so Active suspension system is proposed to meet the requirements with active components which could be controlled by external signal for optimized behavior of train. Active suspension is to be divided by Full active suspension and Semi-active suspension whether using the external power source or not, and though the performance of Semi-Active suspension is worse than Full one. Semi-active suspension is focused with its effectiveness per cost. Semi-Active suspension system consists of sensors, ECU (electrical control unit), and variable damper, which are to be designed to be fit for train system. And the software of ECU is to be developed for to be suited to its dynamic behavior through simulation result calculated by proven model. In this experimental study, the hardware and software of semi-active suspension system is to be realized and its performance for improvement of ride quality to be confirmed through roller rig test.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.7
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• pp.844-850
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• 2016

This study pertains to the extraction of the road noise component of signals from a vehicle's interior noise via the traditional frequency domain and time domain system identification methods. For road noise extraction based on the frequency domain system identification method, the appropriate matrix inversion strategy is investigated and causal and non-causal impulse response filters are compared. Furthermore, appropriate data lengths for the frequency domain system identification method are investigated. In addition to the traditional road noise extraction methods based on frequency domain system identification, a new approach to extract road noise via the time domain system identification method based on a parametric input-output model is proposed and investigated in the present study. In this approach, instead of constructing a higher order model for the full-band road noise, input and output signals are processed in the subband domain and lower order parametric models optimal to each subband are determined. These parametric models are used to extract road noises in each subband; the full band road noise is then reconstructed from the subband road noises. This study shows that both the methods in the frequency domain and the time domain successfully extract the road noise from the vehicle's interior noise.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.4
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• pp.371-379
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• 2015

This paper represents the structural design of the light weight axle beam for medium duty commercial vehicle using hot press. To reduce the weight of the axle, axle beam of solid type was replaced by hollow type which was made by hot press. According to the change of axle beam structure and manufacturing method, we have to investigate the structural strength and fatigue performance. To verify the axle beam performance, the structural analysis was carried out by simplified axle beam model and various design parameters that are axle beam height, thickness and width. From the analysis results, the light weight axle beam structure was founded and applied the full model analysis. This study will be used as a guidance in development of the light weight axle for medium duty commercial vehicle.