• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.281-286
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• 2000

This paper describes a lateral guidance system of an unmanned 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 the unmanned vehicle 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 learning pattern, learning itself, and the adequacy of the design controller. A computer simulation of the vehicle (including vehicle dynamics and steering) was used to verify the steering performance of the vehicle controller using the neural network. Good results were obtained. Also, the real unmanned electrical vehicle using neural network controller verified good results.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1239-1241
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• 2001

This research addresses a new vehicle detecting scheme which uses MR(Megneto Resistive) sensor. A vehicle detector which includes two MR sensors for detecting car presence and speed, sensor voltage amplifiers, signal processor, microprocessor, RF data transceiver and a simple car moving simulator is constructed. From experimental results with the vehicle detector the proposed vehicle detecting scheme was verified.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.308-313
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• 2005

An urban railway vehicle has a characteristics such as that a lot of passenger use it and the major of passenger is standee. The ride comfort of standee is greatly influenced by the lateral dynamic characteristics of vehicle. So the lateral vibration is important factor for the improvement of ride comfort. In this study, vibration test of railway vehicle is carried out under the same condition of field driving to find out the major factor of vibration. By considering the test results under the various driving condition, the vibrational characteristics of vehicle is verified.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.491-491
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• 2000

In this paper, we report the results about the rotational control count on DC motor to drive the mobile vehicle as a first step of the research for the realization of the mobile vehicle with the artificial brain. First of all, we introduce the configuration of the mobile vehicle. This mobile vehicle has one CCD camera driven by a rear wheel. Secondly we show the control methods. This research is adopted the various controls. Finally we report the experimental methods and results and we describe the conclusion of this research.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.274-281
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• 1998

This paper describes a visual control of autonomous vehicle using neural network. Visual control for road-following of autonomous vehicle is based on road image from camera. Road points on image are inputs of controller and vehicle speed and steering angle are outputs of controller using neural network. Simulation study confirmed the visual control of road-following using neural network. For experimental test, autonomous electric vehicle is designed and driving test is realized

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.58-65
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• 2003

Vehicle acceleration data from an accelerometer and wheel speed data from standard, 50-tooth antilock braking system wheel speed sensors are used to estimate the absolute longitudinal speed of a vehicle. We develop the four velocity estimation algorithms. And we compare experimental results with the Butterworth filtered speed from the fifth wheel and find that it is possible to estimate absolute longitudinal vehicle speed during a hard braking maneuver lasting three seconds.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1253-1263
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• 2002

The control system design and modeling of an unmanned vehicle by means of a new concept for better performance through a tole-operation system is suggested by sensor fusion. But, the control of a real vehicle is very difficult, because the system identification of the vehicle is hard to find the unknown factors and the disturbances of the experimental environment. For the longitudinal and lateral controls, the traction system and steering system models are set up and a tuning method to find the gain of the controller by experiments is presented. In this research, mechanical and electronic parts are implemented to operate the unmanned vehicle and data reconstruction method of information about the environment data coming from several sensors is presented by data plot for the vehicle navigation. This paper focuses on the integration of tole-operated unmanned vehicle. This vehicle mainly controlled lateral and longitudinal directions with actuators for controlling vehicle movement and sensors for the closed-loop controlled system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2171-2185
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• 2020

In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.9
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• pp.1003-1008
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• 2012

The paper presents an Experimental Vehicle Model (EVM), that utilizes the kinematic characteristics of suspensions from SPMD test data. The relative displacement and orientation of a wheel with respect to the body are represented as a function of the vertical displacement of the wheel. The equations of motion of the vehicle are formulated in terms of local coordinates that do not require coordinate transformation, which improves the efficiency of dynamic analysis. The EOM was modularized for each suspension model, and a $6{\times}6$ vehicle model was obtained by combining six suspensions. The analysis results were compared with ADAMS to verify the accuracy of the EVM. This study also verifies the feasibility of real-time simulation with the developed EVM. For a vehicle simulation for 1 ms, the real simulation time required within 20% of the prescribed time. This result shows that the EVM meets the real-time simulation requirements.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.411-417
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• 2009

The thermo-flow field in road tunnel is influenced by some facts such as piston effect of vehicle's move, operation of ventilation facilities, natural wind and buoyancy effect of fire plume. Among those, piston effect is one of primary causes for formation of air flow in road tunnel and has an effect on initial direction of smoke flow in tunnel fire. In this study to analyze the unsteady flow in the tunnel caused by the run of vehicle, the experimental study of vehicle-induced unsteady flow on a reduced-scale model tunnel is presented. While the three types of vehicle shape such as basic type of rectangular shape, diamond-head type and stair-tail type are changed, the pressure and air velocity variations with time are measured. The rising ratio of pressure and velocity are in order of "basic type of rectangular shape > stair-tail type > diamond-head type". The experimental results would be good data for development of a numerical method on the vehicle-induced unsteady tunnel flow.