• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.753-759
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• 2009

As many systems depend on electronics in an intelligent vehicle, concern for fault tolerance is growing rapidly. For example, a car with its braking controlled by electronics and no mechanical linkage from brake pedal to calipers of front tires(brake-by-wire system) should be fault tolerant because a failure can come without any warning and its effect is devastating. In general, fault tolerance is usually designed by placing redundant components that duplicate the functions of the original module. In this way a fault can be isolated, and safe operation is guaranteed by replacing the faulty module with its redundant and normal module within a predefined interval. In order to make in-vehicle network fault tolerant, this paper presents the concept and design methodology of an IEEE 1451 based dual CAN module. In addition, feasibility of the dual CAN network was evaluated by implementing the dual CAN module.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.407-410
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• 2012

Recently, wireless network services are widely used, depending on the development of wireless network module technologies and the utilization gradually expanded, and thus is a trend that appears a lot of IT convergence industries. For this study, the OBD-II communication to Import your vehicle information, and other external devices in high-speed driving condition of the vehicle to verify the information system was developed to transfer data to an external server. From various sensors inside the vehicle using the OBD-II connector easily convert all users to read the information, then, Sent to the external server using the wireless network module, high-speed vehicle status check system was implemented. It was to test the performance of the system was developed using the actual circuit in a high-speed road racing vehicles. Transfer data generated from high-speed driving vehicles through the OBD-II scanner and check the status of a high-speed vehicle system was confirmed that this data is normally received. In the future, these new cars convergence of IT technology will grow as a new field of research.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.9
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• pp.1373-1378
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• 2017

This paper presents a basic ECU(Electronic Control Unit) hardware development procedure for the functional safety of in-vehicle network systems. We consider complete hardware redundancy as a safety mechanism for in-vehicle communication network under the assumption of the wired network failure such as disconnection of a CAN bus. An ESC (Electronic Stability Control) system is selected as an item and the required ASIL(Automotive Safety Integrity Level) for this item is assigned by performing the HARA(Hazard Analysis and Risk Assessment). The basic hardware architecture of the ESC system is designed with a microcontroller, passive components, and communication transceivers. The required ASIL for ESC system is shown to be satisfied with the designed safety mechanism by calculation of hardware architecture metrics such as the SPFM(Single Point Fault Metric) and the LFM(Latent Fault Metric).

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.111-111
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• 2000

The research of network system, being used to reduce automotive wiring harness, is reaching to the development of by-wire system. It is by-wire system that apply IVN(In-Vehicle-Network) to steering, braking system, and it has the advantage of mass-decreasing, easy to diagnose fault and so on. But until now, many developed device can't satisfied with reliability that system have ever had. So redundancy of each network module, i.e., It is only way to make backup module. This paper researches development of network module and redundancy management of backup module when error occurred for implementation of brake-by-wire system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.915-919
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• 2005

It is materialized an unmanned vehicle system as a part of Intelligent Transportation System (ITS) which is a fundamental constituent for unmanned vehicle. Remote control system, monitoring system and remote operating system which are consisted of unmanned vehicle system. Network program by TCP/IP socket, and real-time control & operating controlled by servo-motors from a remote place, those are used to verify safety and stability of the unmanned vehicle system in this research. This unmanned vehicle is divided into two major sections which are an unmanned vehicle part and control station part. The server PC is installed on the unmanned vehicle and a client PC is installed at a remote place, which can control the u manned vehicle. In this research work, main theme is that we experimented and tested to check the speed and utilization of the wireless LAN communication.

• 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 Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.85-90
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• 2005

The advance of mobile and telematics technologies has produced vehicles with various convenient services for drivers. Specifically lots of researches and several technologies have been developed to provide services of a remote vehicle diagnosis and control. The existing and representative product for a vehicle control is a RCS (remote control system), but it has a problem of short control distance and fragile security. In this paper, a telematics terminal embedded with CDMA and GPS is designed, which can be connected to the Internet. It allows a driver with a cellular phone to remotely diagnosis and control a vehicle via wireless network and SMS.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.133-139
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• 1997

This paper presents a new approach to the dynamic control technique for track vehicle system using neural network-fuzzy control method. The proposed control scheme uses a Gaussian function as a unit function in the neural network-fuzzy, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is propored a learning controller consisting of two neural network-fuzzy based on independent resoning and a connection net with fixed weights to simply the neural network-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.773-776
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• 2009

Last of the car industry can be grouped in one-vehicle electronic equipment, the development of the network, and accordingly the communication between each of the network is important. The network currently being used in vehicles include CAN, LIN, MOST, FlexRay, etc. are used. Network of several different kinds of applications using the federation said they were also germ, which causes the driver some more convenient environment, the desire to drive a vehicle that is increasing. If vehicle for other network environments with one integrated environment to make it a gateway for research done actively, the more applications are expected to be developed. In this paper, using gateway between CAN bus used for Body Train-side control of the vehicle network and MOST provided for infotainment systems. In vehicle automatic safety control system will be designed by One of CAN Nodes car speed information sending to MOST Navigation while don't received GPS information in the tunnel.