• 제목/요약/키워드: in-vehicle network system

검색결과 787건 처리시간 0.026초

Vehicle Image Recognition Using Deep Convolution Neural Network and Compressed Dictionary Learning

  • Zhou, Yanyan
    • Journal of Information Processing Systems
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    • 제17권2호
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    • pp.411-425
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    • 2021
  • In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.

CAN 통신을 이용한 차량 내 자동 온도조절 시스템 (In-Vehicle Auto temperature control System by CAN Network)

  • 김장주;장종욱
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2009년도 추계학술대회
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    • pp.90-93
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    • 2009
  • 최근 차량용 네트워크 시스템으로 사용되고 있는 CAN(Controller Area Network)은 많은 ECU들이 필요한 미래형 스마트차량에 적합한 네트워크 프로토콜로서 안정성과 신뢰성을 보장해주며, 많은 ECU들의 장착으로 Wiring Harness의 공간과 중량이 늘어남으로 인해 발생되는 에너지 소비와 비용의 증가를 대폭 줄일 수 있는 것으로 나타났다. 본 논문에서는 CAN프로토콜을 이용하여 미래형 스마트 자동차에 요구되는 편의주행, 쾌적주행을 위해 Air conditioner 와 Heater를 제어하여 차량 내부 온도를 운전자의 요구에 맞도록 자동으로 제어할 수 있는 시스템을 구현하고자 한다.

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무선 센서네트워크 기반 차량속도 측정 시스템 (Vehicle Speed Measurement System based on Wireless Sensor Network)

  • 유성은;김태홍;박태수;김대영;신창섭;성경복
    • 대한임베디드공학회논문지
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    • 제3권1호
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    • pp.42-48
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    • 2008
  • The architecture of WSN based Vehicle Speed Measurement System is presented in this paper from Telematics Sensor Network(TSN) to Management System. To verify the feasibility of the system, we implemented the vehicle speed measurement system and evaluated the accuracy of velocity measured by the system in our testbed, an old highway located near Kyungbu highway. The system performed over 95% of accuracy at 80kmph from the measurement. In addition, the battery life time of the sensor node was evaluated by simulation analysis with real measured current consumption profiles. Assuming the maximum average daily traffic in 2005, the battery life time is expected to be over 1.6 year from the simulation result.

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Implementation of Inter-vehicle Communication System and Experiments of Longitudinal Vehicle Platoon Control via a Testbed

  • Kim, Tae-Min;Choi, Jae-Weon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.711-716
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    • 2003
  • This study considers the implementation issues of the inter-vehicle communication system for the vehicle platoon experiments via a testbed. The testbed, which consists of three scale vehicles and one RCS(remote control station), is developed as a tool for functions evaluation between simulation studies and full-sized vehicle researches in the previous study. The cooperative communication of the vehicle-to-vehicle or the vehicle-to-roadside plays a key role for keeping the relative spacing of vehicles small in a vehicle platoon. The static platoon control, where the number of vehicles remains constant, is sufficient for the information to be transmitted in the suitably fixed interval, while the dynamic platoon control such as merge or split requires more flexible network architecture for the dynamical coordination of the communication sequence. In this study, the wireless communication device and the reliable protocol of the flexible network architecture are implemented for our testbed, using the low-cost, ISM band transceiver and the 8-bit microcontroller.

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OSEK/VDX 표준과 CAN 프로토콜을 사용한 차체 네트웍 시스템 개발 (Development of a Body Network System with GSEK/VDX Standards and CAN Protocol)

  • 신민석;이우택;선우명호;한석영
    • 한국자동차공학회논문집
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    • 제10권4호
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    • pp.175-180
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    • 2002
  • In order to satisfy the requirements of time reduction and cost saving for development of electronic control systems(ECU) in automotive industry, the applications of a standardized real-time operating system(RTOS) and a communication protocol to ECUs are increased. In this study, a body control module(BCM) that employs OSEK/VDX(open system and corresponding interfaces for automotive electronics/vehicle distributed executive) OS tour the RTOS and a controller area network(CAN) fur the communication protocol is designed, and the performances of the system are evaluated. The BCM controls doors, mirrors, and windows of the vehicle through the in-vehicle network. To identify all the transmitted and received control messages, a PC connected with the CAN communication protocol behaves as a CAN bus emulator. The control system based upon in-vehicle network improves the system stability and reduces the number of wiring harness. Furthermore it is easy to maintain and simple to add new features because the system is designed based on the standards of RTOS and communication protocol.

매틀랩/시뮬링크 기반 플렉스레이 네트워크 시스템의 구현 및 검증 (Implementation and Verification of FlexRay Network System using Matlab/Simulink)

  • 윤승현;서석현;황성호;권기호;전재욱
    • 제어로봇시스템학회논문지
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    • 제16권7호
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    • pp.655-660
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    • 2010
  • As increasing the number of Electronic Control Units in a vehicle, the proportion for reliability and stability of the software is going increasingly. Accordingly, the traditional CAN network has occurred the situation that the requirement of developing vehicle software is not sufficient. To solve these problems, the FlexRay network which is ensured the high bandwidth and real-time is generated. However it is difficult to implement FlexRay based application software because of complex protocol than traditional CAN network. Accordingly the system for analysis and verification of network state is needed. Also vehicle vendor develops application software using Matlab/Simulink in order to increase productivity. But this development method is hard to solve the network problem of node to node. Therefore this paper implements Matlab/Simulink based FlexRay network system and verifies it through comparing with existing embedded system.

퍼지 로직에 의한 궤도차량의 지능제어시스템 설계 (Intelligent control system design of track vehicle based-on fuzzy logic)

  • 김종수;한성현;조길수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.131-134
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    • 1997
  • This paper presents a new approach to the design of intelligent control system for track vehicle system using fuzzy logic based on neural network. 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 illustrated by simulation for trajectory tracking of track vehicle speed.

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Network-RTK GPS 기반 자동차 정밀 위치 추정 (Network-RTK GNSS for Land Vehicle Navigation Application)

  • 운봉영;이동진;이상선
    • 한국통신학회논문지
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    • 제42권2호
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    • pp.424-431
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    • 2017
  • 요즘 차량 네비게이션 시스템은 큰 관심 분야이다. GNSS(Global Navigation Satellite System)은 실외 측위를 위한 기술 중 핵심적인 기술이다. 그러나 GNSS는 높은 정확도와 신뢰도를 제공하지 못한다. 이러한 이유로, 우리는 차량의 GNSS 성능의 정확도를 향상시키기 위하여 Network-RTK를 적용하였다. 이 Network-RTK 모드에서 GNSS 에러는 급격히 감소하게 된다. 본 논문에서 우리는 ntrip client 프로그램을 설명하고 다양한 환경에서의 실험 결과를 보여준다.

궤도차량의 지능제어 및 3D 시률레이터 개발 (Development of a 3D Simulator and Intelligent Control of Track Vehicle)

  • 장영희;신행봉;정동연;서운학;한성현;고희석
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 춘계학술대회 학술발표 논문집
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    • pp.107-111
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    • 1998
  • This paper presents a now approach to the design of intelligent contorl system for track vehicle system using fuzzy logic based on neural network. 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. Moreover, We develop a Windows 95 version dynamic simulator which can simulate a track vehicle model in 3D graphics space. It is proposed a learning controller consisting of two neural network-fuzzy based of independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The dynamic simulator for track vehicle is developed by Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics. The performance of the proposed controller is illustrated by simulation for trajectory tracking of track vehicle speed.

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신경망을 이용한 전기차동차의 속도오차 보상 (Speed Error Compensation of Electric Differential System Using Neural Network)

  • 유영재;이주상;임영철;장영학;김의선;문채주
    • 제어로봇시스템학회논문지
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    • 제7권1호
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    • pp.1205-1210
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    • 2001
  • This paper describes a methodology using neural network to compensate the nonlinear error of deriving speed for electric differential system included in electric vehicle. An electric differential system which drives each of the left and right wheels of the electric vehicle independently. The electric vehicle driven by induction motor has the nonlinear speed error which depends on a steering angle and speed command. When a vehicle drives along a curved road lane, the speed unblance of inner and outer wheels makes vehicles vibration and speed reduction. To compensate for the speed error, we collected the speed data of the inner wheel and outer wheel in various speed and the steering angle data by using an manufactured electric vehicle and the real system. According to the analysis of the acquisited data, we designed the differential speed control system based on a speed error compensator using neural network.

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