• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.789-794
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• 2013

A vehicle tracking system makes it possible to induce the vehicle movement path for avoiding traffic congestion and to prevent traffic accidents in advance by recognizing traffic flow, monitoring vehicles, and detecting road accidents. To track the vehicles effectively, those which appear in a sequence of video frames need to identified by extracting the features of each object in the frames. Next, the identical vehicles over the continuous frames need to be recognized through the matching among the objects' feature values. In this paper, we identify objects by binarizing the difference image between a target and a referential image, and the labelling technique. As feature values, we use the center coordinate of the minimum bounding rectangle(MBR) of the identified object and the averages of 1D FFT(fast Fourier transform) coefficients with respect to the horizontal and vertical direction of the MBR. A vehicle is tracked in such a way that the pair of objects that have the highest similarity among objects in two continuous images are regarded as an identical object. The experimental result shows that the proposed method outperforms the existing methods that use geometrical features in tracking accuracy.

• Journal of Satellite, Information and Communications
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• v.9 no.3
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• pp.33-40
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• 2014

One of the most important requirements for the Ethernet-based automobile is the reliability. In order to achieve this goal, we propose using the High-availability Seamless Redundancy (HSR) protocol (IEC 62439-3 clause 5) in these networks. The HSR protocol provides duplicated frame copies for each sent frame, which means that the destination node will receive at least one copy in case the second copy is lost due to a failure. In other words, there will be no network stoppage even if failure occurs. Moreover, the destination node will receive at least one frame copy with zero-recovery time (seamless) and it will not need to wait to receive the other copy if the first one is lost, which occurs it in the Ethernet standard, as a result of reconfiguration of the network paths. However, the main drawback of the HSR protocol is the unnecessary redundant traffic that is caused by the duplicated frames. Several solutions, including QR, VRing, RURT, and DVP, have already been proposed to improve the traffic performance of the HSR protocol. In this paper, we propose three automobile network topologies. each of which has pros and cons depending on the automobile requirements. Then we applied the HSR protocol with and without the QR and VRing approaches to each scenario. The comparison among these topologies depend on the traffic performance result for each of them. The QR and VRing approaches give a better traffic reduction percentage, ranging from 48% to 75% compared to the standard HSR protocol. Therefore they could limit the redundant traffic in automobile networks when the HSR protocol is used instead of the Ethernet network, which does not provide any seamless recovery if a failure occurs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.901-908
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• 2010

There are many kinds of networks in vehicle for their purposes. In-vehicle networks, however, are not unified to single network. The networks are composed of several local networks because of communication speed, cost and efficiency. Because the complexity of network design for communication increases, local networks need a framework for interworking between heterogeneous networks. In this paper, a framework interworking between in-vehicle networks for ITS(Intelligent Transportation System) is proposed and implemented. The proposed framework consists of a compatible protocol, message conversion module, message transceiver module and message analysis module. The results obtained by implementation show that the framework efficiently supports the communication of information between heterogeneous in-vehicle networks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.5955-5962
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• 2014

Generally, the frame design of a vehicle is a critical technology that plays an important role in the racing and high performance sports car market. The high performance of race car frame means that it requires high torsional stiffness because it directly affects the cornering behavior of the race car. The optimal design for the frame of a low-cost single seat race car was carried out using the DOE (Design Of Experiments) with Taguchi's orthogonal array and FEM (Finite Element Method) analysis to secure sufficient torsional stiffness in this paper. According to the results by DOE and FEM analysis, the optimal design case produced improved 10.7% and 14.5% improvement in each stiffness-to-weight ratio and frame weight than in the early design step. Therefore, this paper shows that the optimal design with Taguchi's orthogonal array is very useful and effective for designing a tubular space frame of a low-cost single seat race car in the early design step.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.132-151
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• 2022

Vehicle localization is one of the core technologies for autonomous driving. Image-based localization provides location information efficiently, and various related studies have been conducted. However, the image-based localization methods using feature points or lane information has a limitation that positioning accuracy may be greatly affected by road and driving environments. In this study, we propose a line segment matching framework for accurate vehicle localization. The proposed framework consists of four steps: line segment extraction, merging, overlap area detection, and MSLD-based segment matching. The proposed framework stably performed line segment matching at a sufficient level for vehicle positioning regardless of vehicle speed, driving method, and surrounding environment.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1534-1542
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• 2004

A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.

• Journal of KSNVE
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• v.8 no.1
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• pp.45-46
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• 1998

상용차는 대부분 디젤엔진을 사용하고 있고 비교적 강건한 샤시 프레임 구조로 되어있기 때문에 소음 진동특성이 승용차와 상당히 다르며 빈번하게 발생되는 문제도 차이가 있다. 이런 차이에도 불구하고 소음 진동 시험항목은 승용차와 별반 차이가 없으므로 본고에서는 상용차량에서 중요한 몇가지 평가항목에 대해서만 상세하게 언급하고자 한다.

• Review of KIISC
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• v.33 no.4
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• pp.23-29
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• 2023

대부분의 임베디드 시스템은 기계장치와 전자기기 장치가 함께 작동되는 물리 장치로써, 이기종 네트워크, 복잡한 보안체계 등을 고려하여 가상화 기반 사이버훈련 환경이 구성되어야 한다. 또한, 차량을 대상으로 물리적인 실험환경에서 모의침투 등 사이버훈련을 수행한다는 것은 교통사고를 비롯한 안전사고 발생에 있어 위험이 존재한다. 본 논문에서는 가상 개발환경에서의 공격 기반 차량용 사이버훈련 프레임워크를 제안하고자 한다. 먼저, 공격 기반 차량용 사이버훈련 프레임워크의 작동은 자동 활성화되는 가상의 CAN 네트워크 인터페이스로 시작된다. 가상의 CAN 네트워크 인터페이스는 가상 머신에서 간단한 부트스트랩 명령어 실행을 통해 파이썬 패키지와 Ubuntu 서비스 목록 설치 명령이 자동으로 실행되면서 설치된다. 이후 내부 네트워크 시뮬레이터와 공격모듈과 관련된 UI가 자동으로 Ubuntu Systemd에 의해 백그라운드에서 실행되어 시작과 동시에 준비 상태를 유지하게 된다. 사이버훈련 UI 내 공격 모듈은 사용자에 의한 공격 선택 및 파라미터 셋팅 이후 차량의 이상 상태를 사이버훈련 UI에 다시 출력되게 된다. 본 논문에서 제안하는 가상 개발환경 기반의 차량용 사이버훈련 프레임워크는 자율주행 차량 사고의 위험이나 다른 특수한 제약 없이 사용자의 학습 경험을 확장시킬 수 있다. 또한, 기존의 가상화 기반 사이버훈련 교육 콘텐츠와는 달리 일반 사용자들이 접근하기 쉬운 형태로 확장 개발이 가능하다.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.37-43
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• 2003

The purpose of this thesis is to detect multiple vehicles using sequence image analysis at process that detect forward vehicles and lane from sequential color images. Detection of vehicles candidate area uses shadow characteristic and edge information in one frame. And, method to detect multiple vehicles area analyzes Estimation of Vehicle(EOV) and Accumulated Similarity Function(ASF) of vehicles candidate areas that exist in sequential images and examine possibility to be vehicles. Most researches detected a forward vehicles in road images but this research presented method to detect several vehicles and apply enough in havy traffic. To verify the effects of the proposed method, we capture the road images with notebook and CCD camera for PC and present the results such as processing time, accuracy and vehicles detection in the images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.54-62
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• 2018

According to evolution of technologies, many devices related to various applications were researched. The advanced driver assistance system is a famous technique effected from the evolution. The technique of driver assistance uses image recognition methods to collect exactly information around the vehicle. The computing power of driver assistance device has become more improved than in the past. However, it's difficult that processed various recognition methods at real-time. We propose new frame skip method to process various recognition methods at real-time in the limited hardware. In the previous researches, frame skip rate was set up static values, thus the number of processed frames through recognition methods was smaller. We set up the frame skip rate dynamically using a driving condition of vehicle through speed and acceleration value, in addition, the number of processed frames was maximized. The performance is improved more 32.5% than static frame skip method.