• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.73-76
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• 2005

The advanced information and communication technology gives vehicles another role of the third digital space, merging a physical space with a virtual space in a ubiquitous society. In the ubiquitous environment, the vehicle becomes a sensor node, which has a computing and communication capability in the digital space of wired and wireless network. An intelligent vehicle information system with a remote control and diagnosis is one of the future vehicle systems that we can expect in the ubiquitous environment. However, for the intelligent vehicle system, many issues such as vehicle mobility, in-vehicle communication, service platform and network convergence should be resolved. In this paper, an in-vehicle gateway is presented for an intelligent vehicle information system to make an access to heterogeneous networks. It gives an access to the server systems on the internet via CDMA-based hierarchical module architecture. Some experiments was made to find out how long it takes to communicate between a vehicle's intelligent information system and an external server in the various environment. The results show that the average response time amounts to 776ms at fixec place, 707ms at rural area and 910ms at urban area.

• 한국항행학회논문지
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• 제15권1호
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• pp.157-161
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• 2011

본 논문은 세션 관리 기능을 포함한 차량 네트워크 환경을 위한 오류 처리에 대해서 기술한다. 이 시스템은 FDA(Fault Detection Agent)와 FRA(Fault Recovery Agent)로 구성되어 있다. FDA는 세션 관리 기능을 포함한 차량 네트워크 환경에서 멀티미디어 시스템을 위하여 훅 킹 기법으로 오류를 감지하는 에이전트이다. FRA는 차량 네트워크 환경에서 세션 관리 기능을 포함한 멀티미디어 시스템을 위한 소프트웨어 오류를 복구하기에 적합한 에이전트이다. 본 논문에서는 FRA에 범위를 한정한다. 여러 개의 지역 세션이 동시에 개설 되었을 경우에 각 지역 세션 관리자는 자신의 세션에 속한 참여자들에 대한 정보를 전체 세션 관리자에게 제공해서 네트워크에서 진행 중인 세션에 대한 최신의 정보를 유지한다.

• 한국산업정보학회논문지
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• 제19권3호
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• pp.9-15
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• 2014

In the ubiquitous computing environment, a ubiquitous vehicle will be a communication node in the vehicular network as well as the means of ground transportation. It will make humans and vehicles seamlessly and remotely connected. Especially, one of the prominent services in the ubiquitous vehicle is the vehicle remote operation. However, mutual-collaboration with the in-vehicle communication network, the vehicle-to-vehicle communication network and the vehicle-to-roadside communication network is required to provide vehicle remote operation services. In this paper, an Internet-based human-vehicle interfaces and a network architecture is presented to provide remote vehicle control and diagnosis services. The performance of the proposed system is evaluated through a design and implementation in terms of the round trip time taken to get a vehicle remote operation service.

• 한국통신학회논문지
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• 제40권3호
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• pp.602-612
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• 2015

현재 표준 차량 통신 프로토콜인 IEEE 802.11p는 차량 간 한 홉 전송을 수행하기 때문에 차량 환경에서 효율적인 정보 전달을 수행하는데 한계가 있다. 본 논문은 차량 환경에서 효율적인 정보 전달을 위해 무선 근거리 통신 중 하나인 LTE-D2D 기술을 사용한 차량 네트워크를 제안한다. 이때 전송 메시지 형태는 IP 패킷 옵션을 지닌 이름 기반 정보 메시지를 사용하고 일반 차량 노드는 요청하는 메시지를 중간 매개 노드인 대형 차량 노드로 전송하여 정보를 전송 받는다. 성능 분석을 통해 셀룰러 네트워크와 제안된 LTE-D2D 차량 네트워크에서의 패킷전달 시간에 따른 데이터 처리율을 비교하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.1023-1026
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• 2005

In the ubiquitous computing environment, an intelligent vehicle is defined as a sensor node with a capability of intelligence and communication in a wire and wireless network space. To make it real, a lot of problems should be addressed in the aspect of vehicle mobility, in-vehicle communication, common service platform and the connection of heterogeneous networks to provide a driver with several intelligent information services beyond the time and space. In this paper, we present an intelligent information system for managing in-vehicle sensor network and a vehicle gateway for connecting the external networks. The in-vehicle sensor network connected with several sensor nodes is used to collect sensor data and control the vehicle based on CAN protocol. Each sensor node is equipped with a reusable modular node architecture, which contains a common CAN stack, a message manager and an event handler. The vehicle gateway makes vehicle control and diagnosis from a remote host possible by connecting the in-vehicle sensor network with an external network. Specifically, it gives an access to the external mobile communication network such as CDMA. Some experiments was made to find out how long it takes to communicate between a vehicle's intelligent information system and an external server in the various environment. The results show that the average response time amounts to 776ms at fixed place, 707ms at rural area and 910ms at urban area.

• Journal of Mechanical Science and Technology
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• 제15권4호
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• pp.448-458
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• 2001

The primary goal of virtual prototyping is to eliminate the need for fabricating physical prototypes, and to reduce cost and time for developing new products. A virtual prototyping seeks to create a virtual environment where the development of a new model can be flexible as well as rapid, and experiments can be carried out effectively concerning kinematics, dynamics, and control aspects of the model. This paper addresses the virtual environment used for virtual prototyping of a passenger vehicle. It has been developed using the dVISE environment that provides such useful features as actions, events, sounds, and light features. A vehicle model including features, and behaviors is constructed by employing an object-oriented paradigm and contains detailed information about a real-size vehicle. The human model is also implemented not only for visual and reach evaluations of the developed vehicle model, but also for behavioral visualization during a crash test. For the real time driving simulation, a neural network model is incorporated into the virtual environment. The cases of passing bumps with a vehicle are discussed in order to demonstrate the applicability of a set of developed models.

• 한국정밀공학회지
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• 제16권7호
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• pp.109-118
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• 1999

A graphic software is one of the most important components of the vehicle simulator. To increase a visual reality of the simulator, the graphic software should require several technologies such as three-dimensional graphics, graphic modeling of the vehicle and the environment, drivers biomechanical models, and real-time data processing. This study presents a real time graphic driving simulator of a construction vehicle. The graphic simulator contains the three models of the construction vehicle, the human, and the environment, and employes a neural network approach to decrease an on-line dynamic computation. An excavator model is represented using an object-oriented paradigm and contains the detailed information about a real-size vehicle. The human model is introduced for objective visual evaluations of the developed excavator model. Since the environment model plays an important role in a real-time simulator, a block-based approach is implemented and a text format is utilized for easier construction of environment. The simulation results are illustrated in order to demonstrate the applicability of developed models and the neural network approach.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 추계학술대회
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• pp.773-776
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• 2009

최근의 차량 산업은 차량 내 전자장비들을 하나로 묶을 수 있는 네트워크들이 발달되고, 이에 따라 각각의 네트워크간의 통신이 중요시 되고 있다. 현재 차량에 사용되고 있는 네트워크로는 CAN, LIN, MOST, FlexRay 등이 사용되고 있다. 여러 가지 네트워크들이 생겨나면서 네트워크를 이용한 여러 가지 응용들도 생겨나게 되었고, 이로 인해 운전자들도 좀 더 편리한 환경에서 차량을 운전하고자 하는 욕구가 많아지고 있다. 차량내의 다른 네트워크 환경을 하나의 통합된 환경으로 만들어주기 위한 게이트웨이 연구가 활발히 이루어진다면, 보다 많은 응용들이 개발될 것으로 예상된다. 본 논문에서는 주로 차량의 Body Train 쪽 제어에 사용되는 CAN bus 네트워크와 인포테인먼트 시스템을 제공해주는 MOST 네트워크간의 게이트웨이를 이용한다. 통신을 통해 CAN Node중의 하나인 차량속도를 MOST Navigation 으로 전송하여 차량이 터널에 진입하여 GPS 정보를 얻어올 수 없을 때도 차량의 현재 속도정보를 Gateway를 통해 Navigation으로 실시간으로 전송하는 기술을 이용하는 차량 자동 안전제어 시뮬레이션 시스템 설계하고 구현하고자 한다.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.124-131
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• 2000

In this study, the NEURAL NETWORK (hereinafter referred to as NN) was applied to control of the nonlinear factors for turning movement of the crawler vehicle and experiment was carried out using a small model of crawler vehicle in order to inspect an application of NN. Furthermore, CHAOS NEURAL NETWORK (hereinafter referred to as CNN) was also applied to this control so as to compare with conventional NN. CNN is especially effective for plane in many variables with local minimum which conventional NN is apt to fall into, and it is relatively useful to nonlinear factors. Experiment of turning on the slope of crawler vehicle was performed in order to estimate an adaptability of nonlinear problems by NN and CNN. The inclination angles of the road surface which the vehicles travel on, were respectively 4deg, 8deg, 12deg. These field conditions were selected by the object for changing nonlinear magnitude in turning phenomenon of vehicle. Learning of NN and CNN was carried out by referring to positioning data obtained from measurement at every 15deg in turning. After learning, the sampling data at every 15deg were interpolated based on the constructed learning system of NN and CNN. Learning and simulation programs of NN and CNN were made by C language ("Association of research for algorithm of calculating machine (1992)"). As a result, conventional NN and CNN were available for interpolation of sampling data. Moreover, when nonlinear intensity is not so large under the field condition of small slope, interpolation performance of CNN was a little not so better than NN. However, when nonlinear intensity is large under the field condition of large slope, interpolation performance of CNN was relatively better than NN.

• International Journal of Computer Science & Network Security
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• 제23권11호
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• pp.67-72
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• 2023

In the past decade, Autonomous Vehicle Systems (AVS) have advanced at an exponential rate, particularly due to improvements in artificial intelligence, which have had a significant impact on social as well as road safety and the future of transportation systems. The fusion of light detection and ranging (LiDAR) and camera data in real-time is known to be a crucial process in many applications, such as in autonomous driving, industrial automation and robotics. Especially in the case of autonomous vehicles, the efficient fusion of data from these two types of sensors is important to enabling the depth of objects as well as the classification of objects at short and long distances. This paper presents classification of objects using CNN based vision and Light Detection and Ranging (LIDAR) fusion in autonomous vehicles in the environment. This method is based on convolutional neural network (CNN) and image up sampling theory. By creating a point cloud of LIDAR data up sampling and converting into pixel-level depth information, depth information is connected with Red Green Blue data and fed into a deep CNN. The proposed method can obtain informative feature representation for object classification in autonomous vehicle environment using the integrated vision and LIDAR data. This method is adopted to guarantee both object classification accuracy and minimal loss. Experimental results show the effectiveness and efficiency of presented approach for objects classification.