• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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• pp.367-375
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over modeling error, parameter variation and disturbance. Second, it needs accurate performance which have small overshoot phenomenon and steady state error to avoid colliding with ground surface or obstacles. Third, it needs continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, it needs interpolation method which can sole the speed dependency problem of controller parameters. To solve these problems, we propose a depth control method using Fuzzy Sliding Mode Controller with feedforward control-plane bias term and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.178-185
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• 1999

Recently, Collision Warning System is developed to improve vehicle safety. This system chiefly uses radar. But the detected vehicle from radar must be decide whether it is the vehicle in the same lane of my vehicle or not. Therefore, Vision System is needed to detect traffic lane. As a preparative step, this study presents the development of algorithm to recognize traffic lane curve direction. That is, the Neural Network that can recognize traffic lane curve direction is constructed by using the information of short distance, middle distance, and decline of traffic lane. For this procedure, the relation between used information and traffic lane curve direction must be analyzed. As the result of application to sampled 2,000 frames, the rate of success is over 90%.t text here.

• Journal of Navigation and Port Research
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• v.33 no.2
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• pp.143-151
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• 2009

The field of vehicle routing is currently growing rapidly because of many actual applications in truckload and less than truckload trucking, courier services, door to door services, and many other problems that generally hinder the optimization of transportation costs in a logistics network. The rapidly increasing number of customers in such a network has caused problems such as difficulty in cost optimization in terms of getting a global optimum solution in an acceptable time. Fast algorithms are needed to find sufficient solutions in a limited time that can be used for real time scheduling. In this paper, the nearest L-method (NLNM) is proposed to obtain a vehicle routing solution. String neighbors of different lengths were chosen, tested and compared. The applied de crossing procedure is meant to solve the routes by NLNM by giving a better solution and shorter computation time than that of NLNM with long string neighbors.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.262-266
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• 2010

Recognizing a license plate of a vehicle has widely been issued. In this thesis, firstly, mean shift algorithm is used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate. We then present an approach to recognize a vehicle's license plate using the Fuzzy ARTMAP neural network, a relatively new architecture of the neural network family. We show that the proposed system is well to recognize the license plate and shows some compute simulations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.636-639
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• 2003

In this paper, we present a robust method for detecting other vehicles from n forward-looking CCD camera in a moving vehicle. This system uses edge and shape information to detect other vehicles. The algorithm consists of three steps: lane detection, ehicle candidate generation, and vehicle verification. First after detecting a lane from the template matching method, we divide the road into three parts: left lane, front lane, and right lane. Second, we set the region of interest (ROI) using the lane position information and extract a vehicle candidate from the ROI. Third, we use local orientation coding (LOC) edge image of the vehicle candidate as input to a pretrained neural network for vehicle recognition. Experimental results from highway scenes show the robustness and effectiveness of this method.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.8
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• pp.88-100
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• 1997

This paper proposes a new concept for an optimal traffic signal cycle method which will reduce the average vehicle waiting time and improve average vehicle speed. Electro sensitive traffic system can extend the traffic cycle when there ar emany vehicles in the road or it can reduce the traffic consider vehicle length, so it can cause oveflow and reduce average vechicel waiting time at the intersection, we propose on optimal traffic cycle with fuzzy ruels and neural network. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle's length for the optimal traffic cycle better than fixe dsignal method dosen't consider vehicle length.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.526-532
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• 2003

This paper describes a recognition method of a road direction for an autonomous vehicle based on magnetic sensors. Using the sensors mounted on a vehicle and the magnetic markers embedded along the center of road, the autonomous vehicle can recognize a road direction and control a steering angle. Using the front lateral deviation of a vehicle and the rear one, the road direction is calculated. The analysis of magnetic field, the acquisition technique of training data, the training method of neural network and the computer simulation are presented. According to the computer simulation, the proposed method is simulated, and its performance is verified. Also, the experimental test is confirmed its reliability.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.167-178
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• 2019

In this paper, we study the multi-objectives vehicle and drone routing problem with time windows, MOVDRPTW for short, which is defined in an urban delivery network. We consider the dual modal delivery system consisting of drones and vehicles. Drones are used as a complement to the vehicle and operate in a point to point manner between the depot and the customer. Customers make various requests. They prefer to receive delivery services within the predetermined time range and some customers require fast delivery. The purpose of this paper is to investigate the effectiveness of the delivery strategy of using drones and vehicles together with a multi-objective measures. As experiment datasets, we use the instances generated based on actual courier delivery data. We propose a hybrid multi-objective evolutionary algorithm for solving MOVDRPTW. Our results confirm that the vehicle-drone mixed strategy has 30% cost advantage over vehicle only strategy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.82-88
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• 2012

A VANET (Vehicular Ad Hoc Network), a subclass of MANET (Mobile Ad Hoc Network), is an ad hoc network using wireless communication between vehicles without fixed infrastructure such as base station. VANET suffers a frequent link breakage and network topology change because of the rapid movement of vehicles and the density change of vehicles. From these characteristics of VANET, geographical routing protocols such as GPSR (Greedy Perimeter Stateless Routing) using only the information of neighbor nodes are more suitable rather than AODV and DSR that are used in existing MANETs. However, GPSR may have a transmission delay and packet loss by frequent link disconnection and continual local maxima under the low vehicle density conditions. Therefore, in this paper, we propose a DTVR (Delay Tolerant Vehicular Routing) algorithm that perform a DTN-based routing scheme if there is no 2-hop neighbor nodes for efficient routing under the low vehicle densities in VANETs. Simulation results using ns-2 reveal that the proposed DTVR protocol performs much better performance than the existing routing protocols.

• 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.