• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권8호
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• pp.3399-3419
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• 2020

In the Vehicular Ad-hoc Network (VANET), the data transmission of time-sensitive applications requires low latency, such as accident warnings, driving guidance, etc. However, frequent changes of topology in VANET will result in data transmission failures. In order to improve the efficiency of VANETs data transmission and increase the timeliness of data, this paper proposes a relay scheme based on Recurrent Neural Network (RNN) trajectory prediction, which can be used to select the optimal relay vehicle to transmit data. The proposed scheme learns vehicle trajectory in a distributed manner and calculates the predicted trajectory, and then the optimal vehicle can be selected to complete the data transmission, which ensures the timeliness of the data. Finally, we carry out a set of simulations to demonstrate the performance of the algorithm. Simulation results show that the proposed scheme enhances the timeliness of the data and the accuracy of the predicted driving trajectory.

• 제어로봇시스템학회논문지
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• 제15권7호
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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.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2012년도 추계학술대회
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• pp.407-410
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• 2012

최근, 무선 네트워크의 서비스가 널리 사용됨에 따라, 무선 네트워크 모듈의 개발 기술 및 그 활용도가 점차 확대되고 있으며, 그에 따라서 IT 융합 산업들이 많이 나타나고 있는 추세이다. 본 연구는 자동차 정보를 가져오기 위해 OBD-II 통신을 이용하고, 외부 서버로 데이터를 전송하여 다른 외부 장치에서도 고속 주행 중인 차량의 상태 정보를 확인 할 수 있는 시스템을 개발하였다. 차량 내부의 각종 센서들로부터 OBD-II 커넥터를 이용하여 정보를 읽고 사용자가 보기 쉽게 변환한 뒤, 무선 네트워크 모듈을 이용하여 외부 서버로 전송을 하는 고속 차량 상태 확인 시스템을 구현하였다. 개발한 시스템의 성능 테스트를 위하여 실제 써킷에서 고속 주행 중인 경주용 차량을 이용했다. 고속 주행 중인 차량에서 발생된 데이터는 OBD-II 스캐너를 통하여 전송되었으며, 고속 차량 상태 확인 시스템은 이 데이터가 정상적으로 수신 되는 것을 확인하였다. 수신된 데이터는 무선 네트워크를 이용하여 외부 서버로 전송을 하였을 때 똑같은 데이터가 에러 없이 송 수신되는 것을 확인하였다. 향후 이런 기술은 새로운 자동차 IT 융합의 새로운 연구 분야로써 성장하게 될 것이다.

• 한국정보통신학회논문지
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• 제22권12호
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• pp.1691-1697
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• 2018

무인이동체에 대한 연구가 지속적으로 이루어 져왔다. 현재까지 지속적인 연구의 결과 무인이동체의 상용화 소식이 들려온다. 또한, 다양한 분야에서 무인이동체를 적용해 왔다. 무인이동체를 실내에서 적용시키기 위해서도 또한, 많은 연구가 이루어져왔다. IoT전용 망인 LoRa망을 이용하여 작은 공간인 집이나 혹은 사무실 병원 에서부터 공장까지 LoRa망을 적용한 무인이동체 관제 시스템을 설치하여 무인이동체가 특수한 작업을 할 때, 더욱 효율성을 높여준다. 본 논문은 IoT전용 망인 LoRa망을 이용하여 무인이동체를 하나의 사물로 인식하고, 주변 사물과 소통을 하며 무인이동체가 실내에서 주행에 필요한 정보들을 클라우드 서버로부터 제공 받음으로써, 다양한 문제점들에 대한 해결책을 제시한다.

• 한국정보시스템학회지:정보시스템연구
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• 제29권2호
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• 제어로봇시스템학회논문지
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• 제13권10호
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• pp.933-939
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• 2007

Safety critical systems such as x-by-wire systems require in-vehicle network systems that can interconnect various sensors, actuators, and controllers. These networks need to have high data rate, deterministic operation, and fault tolerance. Recently, FlexRay protocol that is a time-triggered protocol has been introduced, and many automotive companies have been focusing on this protocol. This paper presents a design method of FlexRay network system and implementation of FlexRay-based motor control system.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.142-147
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• 1999

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 proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by simulation for trajectory tracking of the speed and azimuth of a track vehicle.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 춘계학술대회
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• pp.864-869
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• 2004

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of 'NARMAX' form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

• 제어로봇시스템학회논문지
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• 제18권8호
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• pp.706-712
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• 2012

This paper presents a sensor network and operation for multiple autonomous navigation platform and transport service. Multiple platform navigate with inside sensors and outside sensors while acquiring and process some useful information. Each platform communicates each other by navigational information through central main server. Efficient sensor network systems are considered for the scenario which some passengers call the service and the vehicle accomplish its transport service by transporting each caller to the destination by autonomous manners. In the scenario, all vehicles perform a role of sensor system to the central server and the server handles each information and integrate with faster procedure in the wireless 3G network.