• IEMEK Journal of Embedded Systems and Applications
• /
• v.6 no.3
• /
• pp.149-156
• /
• 2011

Transmission delay and packet loss induced by a communication network can degrade the control performance and, even make the system unstable. This paper presents a method for compensating transmission delay and packet loss in a networked control system for unmanned underwater vehicle. The proposed method is based on Lagrange interpolation in order to satisfy the requirements of simplicity and model-independency. In this work, the lost/delayed data are estimated in real time by only using the past data without requiring any mathematical model of the controlled system. Consequently, the proposed method can be implemented independent of the controlled system, and also it can achieve fast and accurate compensation performance. The performance of the proposed technique is evaluated by numerical simulations with an unmanned underwater vehicle.

• Proceedings of the Safety Management and Science Conference
• /
• 2005.05a
• /
• pp.259-266
• /
• 2005

In this paper, we developed a vehicle condition monitoring system that checks vehicle conditions, and transmits and displays them to a driver for safety and effective maintenance. We used a CAN controller and transceiver to establish the CAN communication that has been used commonly inside an actual vehicle for the collection of vehicle's status information. To validate the operation of the developed system, we have confirmed the accuracy and stability of data transmission and reception of vehicle information.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.5
• /
• pp.641-647
• /
• 2009

In this paper, a new filtering scheme for adaptive cruise control (ACC) system is presented. In the proposed scheme, the identification of the mode of the preceding vehicle is considered as a classification problem and it is done by a neural network classifier. The neural network classifier outputs a posterior probability of the mode of the preceding vehicle and the probability is directly used in the IMM framework. Finally, ten scenarios are made and the proposed NIMM is tested on them to show its validity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2006.11a
• /
• pp.203-207
• /
• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• Journal of the Institute of Convergence Signal Processing
• /
• v.12 no.3
• /
• pp.199-203
• /
• 2011

The wireless sensor network (WSN) based on ad hoc network is applied to vehicle parking guide system without parking guide man at area or building with large scale of parking lots. The optimum number of cluster heads was derived for getting the minimum power consumption as well as time delay. Through the theoretical analysis of power consumption and time delay with the number of cluster heads in wireless sensor network, it was found that there exists the minimum point in the variation of power consumption and time delay according to the number of cluster heads.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.591-595
• /
• 1998

This paper proposes a new concept of optimal shortest path algorithm which reduce average vehicle wating time and improve average vehicle speed, Electro sensitive traffic system can extend the traffic cycle when three are many vehicles on the road or it can reduce the traffic cycle when there are small vehicles on the road. But electro sensitive traffic light system doesn't control that kind of function when the average vehicle speed is 10km -20km. Therefore, in this paper to reduce vehicle waiting time we developed design of traffic cycle software tool that can arrive destinination as soon as possible using optimal shortest pass algorithm. Computer simulation result proved 10%-32% reducing average vehicle wating time and average vehicle speed which can select shortest route using built in G.P.S. vehicle is better than not being able to select shortest route function.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.271-274
• /
• 2001

Recently, most vehicles has the Automatic transmission system as their transmission system. The automatic transmission system operates with fixed shift patterns. In the opposite of manual operation, it is easy and convenient for driving. Though these merit, the system can not evaluate the driver's intension because of usage of fixed shift pattern, To consider driver's intension, we must consider both the driving intensity of driver and the status of vehicle. In this paper, we developed flexible automatic transmission system by using the proposed moduled neural networks which can learn the status of the vehicle and driver's intensity As a result, we compare the transmission system using fixed shift pattern and the proposed transmission system and show the good performance in the change of shift position.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.10
• /
• pp.967-982
• /
• 2011

This paper presents a FTNCS (Fault-Tolerant Networked Control System) that can tolerate control surface failure and packet delay/loss in an UAV (Unmanned Aerial Vehicle). The proposed method utilizes the benefits of self-diagnosis by smart actuators along with the control allocation technique. A smart actuator is an intelligent actuation system combined with microprocessors to perform self-diagnosis and bi-directional communications. In the event of failure, the smart actuator provides the system supervisor with a set of actuator condition data. The system supervisor then compensate for the effect of faulty actuators by re-allocating redundant control surfaces based on the provided actuator condition data. In addition to the compensation of faulty actuators, the proposed FTNCS also includes an efficient algorithm to deal with network induced delay/packet loss. The proposed algorithm is based on a Lagrange polynomial interpolation method without any mathematical model of the system. Computer simulations with an UAV show that the proposed FTNCS can achieve a fast and accurate tracking performance even in the presence of actuator faults and network induced delays.

• Journal of information and communication convergence engineering
• /
• v.9 no.4
• /
• pp.447-451
• /
• 2011

Recently, various in-vehicle networks have been developed respectively in order to accomplish their own purposes such as CAN and MOST. Especially, the MOST network is usually adapted to provide entertainment service. The car navigation system is also widely used for guiding driving paths to driver. The position for the navigation system is usually acquired by GPS technology. However, the GPS technique has two serious problems. The first is unavailability in urban canyons. The second is inherent positional error rate. The problems have been studied in many literatures. However, the second still leads to incorrect locational information in some area, especially parallel roads. This paper proposes a performance tuning method of image matching algorithm for the car navigation system. The method utilizes images obtained from in-vehicle MOST network and a real-time image matching algorithm which determines the direction of moving vehicle in parallel section of road. In order to accuracy improvement of image matching algorithm, three conditions are applied. The experimental tests show that the proposed system increases the accuracy.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.468-471
• /
• 2005

The Air Quality Sensor(AQS), located near the fresh air inlet, serves to reduce the amount of pollution entering the vehicle cabin through the HVAC(heating, ventilating, and air conditioning) system by sending a signal to close the fresh air inlet door/ventilation flap when the vehicle enters a high pollution area. One chip sensor module which include above two sensing elements, humidity sensor and bad odor sensor was developed for AQS (air quality sensor) in automobile. With this sensor module, PIC microcontroller was designed with back propagation neural network to reduce detecting error when the motor vehicles pass through the dense fog area. The signal from neural network was modified to control the inlet of automobile and display the result or alarm the situation. One chip microcontroller, Atmega128L (ATmega Ltd., USA) was used. For the control and display. And our developed system can intelligently detect the bad odor when the motor vehicles pass through the polluted air zone such as cattle farm.