• Title/Summary/Keyword: 블랙박스 시뮬레이션

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Sharing Black Box Information in VANET for Vehicle Accidents Simulation (차량사고 시뮬레이션을 위한 VANET 기반의 블랙박스 정보공유)

  • Kim, Nam-Jung;Yu, Ji-Eun;Lee, Won-Jun
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06d
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    • pp.285-287
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    • 2012
  • 근래 정부에서는 차량용 블랙박스의 필요성과 효율성을 인식해 모든 차량에 블랙박스(EDR, Event Data Recorder)를 의무적으로 장착하게 하고, 이를 통해 차량의 운행 정보와 상황을 모니터 및 관리를 할 수 있도록 정부 시책을 신설하고 이를 추진하고 있는 중이다. 특히 차량사고 발생시 이를 시뮬레이션하고 분석할 수 있는 자료가 매우 부족하다. 교통사고의 시뮬레이션 사고 차량의 운행정보뿐만 아니라 주변 운행환경 및 운행여건, 다른 차량의 간섭 등 매우 많은 정보가 필요하기 때문이다. 이에 본 논문에서는 블랙박스 간 Ad-hoc network을 이용해 차량의 정보를 공유 할 수 있는 시스템을 제안하고자 한다. 즉, 차량에서 돌발상황이 발생했을 때 발생 차량의 블랙박스 의 정보와 주변 운행하고 있는 차량에 장착되어 있는 블랙박스의 정보를 Ad-hoc network를 통해 사고 발생차량으로 수집, 이를 저장하고 추후사고에 대한 시뮬레이션 에서 이 데이터들을 통해 돌발상황 당시의 주변 차량 흐름과 다른 차량간의 간섭 및 돌발상황 유발 같은 현상을 조금 더 정확하게 시뮬레이션 함으로서 돌발상황에 대한 분석 및 판단에 도움을 줄 것이라 생각한다.

Black-Box System for Storing Traffic Accident Information based in USN Environments (USN 환경에서 교통사고시 상대 차량 정보 저장을 위한 블랙박스 시스템)

  • Jae-In Kim;Dae-Young Han;Chul-Su Na;Dae-In Kim;Bu-Hyun Hwang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.11a
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    • pp.895-898
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    • 2008
  • 블랙박스 시스템은 평시 및 사고 직전후의 각종 운행 기록 정보, 영상 정보 등 다양한 사고 정보를 저장할 수 있으며 이에 기반하여 교통 사고를 재현해내는 기술에 대한 활발한 연구가 진행 중이다. 본 논문은 USN 환경에서 차량 간 교통사고 발생시 상대 차량 정보를 블랙박스 내에 저장할 수 있는 시스템을 제안한다. 블랙박스에 저장되는 상대 차량에 대한 정보는 각종 사고 발생시 교통 사고 분쟁 해결에 결정적 요인이 될 수 있으므로 그 중요성이 크다. 제안하는 블랙박스 시스템에 저장되는 정보는 차량 고유 번호, 사고 발생 시간 및 위치 등의 정보이고 그 정보는 허가된 사용자에게만 접근 될 수 있다. 본 논문에서는 두 개의 센서 노드를 블랙박스로 가정하고 임의의 충돌 신호를 발생시켜 상대 차량의 정보를 저장하고, 이를 분석하는 시뮬레이션을 통하여 제안하는 블랙박스 시스템이 사고 차량 정보와 위치, 시간 등을 저장함을 보인다. 수집된 정보는 교통 사고에 대한 과학적인 해석과 사건 재현을 위한 객관적인 정보로 사용 될 수 있다.

Real-time Integrity for Vehicle Black Box System (차량용 블랙박스 시스템을 위한 실시간 무결성 보장기법)

  • Kim, Yun-Gyu;Kim, Bum-Han;Lee, Dong-Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.19 no.6
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    • pp.49-61
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    • 2009
  • Recently, a great attention has been paid to a vehicle black box device in the auto markets since it provides an accident re-construction based on the data which contains audio, video, and some meaningful driving informations. It is expected that the device will get to promote around commercial vehicles and the market will greatly grow within a few years. Drivers who equips the device in their car believes that it can find the origin of an accident and help an objective judge. Unfortunately, the current one does not provide the integrity of the data stored in the device. That is the data can be forged or modified by outsider or insider adversary because it is just designed to keep the latest data produced by itself. This fact cause a great concern in car insurance and law enforcement, since the unprotected data cannot be trusted. To resolve the problem, in this paper, we propose a novel real-time integrity protection scheme for vehicle black box device. We also present the evaluation results by simulation using our software implementation.

Analyzing the Characteristics of Pre-service Elementary School Teachers' Modeling and Epistemic Criteria with the Blackbox Simulation Program (블랙박스 시뮬레이션에 참여한 초등예비교사의 모형 구성의 특징과 인식적 기준)

  • Park, Jeongwoo;Lee, Sun-Kyung;Shim, Han Su;Lee, Gyeong-Geon;Shin, Myeong-Kyeong
    • Journal of The Korean Association For Science Education
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    • v.38 no.3
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    • pp.305-317
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    • 2018
  • In this study, we investigated the characteristics of participant students' modeling with the blackbox simulation program and epistemic criteria. For this research, we developed a blackbox simulation program, which is an ill-structured problem situation reflecting the scientific practice. This simulation program is applied in the activities. 23 groups, 89 second year students of an education college participated in this activity. They visualized, modeled, modified, and evaluated their thoughts on internal structure in the blackbox. All of students' activities were recorded and analyzed. As a result, the students' models in blackbox activities were categorized into four types considering their form and function. Model evaluation occurred in group model selection. Epistemic criteria such as empirical coherence, comprehensiveness, analogy, simplicity, and implementation were adapted in model evaluation. The educational implications discussed above are as follows: First, the blackbox simulation activities in which the students participated in this study have educational implications in that they provide a context in which the nature of scientific practice can be experienced explicitly and implicitly by constructing and testing models. Second, from the beginning of the activity, epistemic criteria such as empirical coherence, comprehensiveness, analogy, simplicity, and implementation were not strictly adapted and dynamically flexibly adapted according to the context. Third, the study of epistemic criteria in various contexts as well as in the context of this study will broaden the horizon of understanding the nature of scientific practice. Simulation activity, which is the context of this study, can lead to research related to computational thinking that will be more important in future society. We expect to be able to lead more discussions by furthering this study by elaborating and systematizing its context and method.

A License Plate Recognition Algorithm using Multi-Stage Neural Network for Automobile Black-Box Image (다단계 신경 회로망을 이용한 블랙박스 영상용 차량 번호판 인식 알고리즘)

  • Kim, Jin-young;Heo, Seo-weon;Lim, Jong-tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.1
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    • pp.40-48
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    • 2018
  • This paper proposes a license-plate recognition algorithm for automobile black-box image which is obtained from the camera moving with the automobile. The algorithm intends to increase the overall recognition-rate of the license-plate by increasing the Korean character recognition-rate using multi-stage neural network for automobile black-box image where there are many movements of the camera and variations of light intensity. The proposed algorithm separately recognizes the vowel and consonant of Korean characters of automobile license-plate. First, the first-stage neural network recognizes the vowels, and the recognized vowels are classified as vertical-vowels('ㅏ','ㅓ') and horizontal-vowels('ㅗ','ㅜ'). Then the consonant is classified by the second-stage neural networks for each vowel group. The simulation for automobile license-plate recognition is performed for the image obtained by a real black-box system, and the simulation results show the proposed algorithm provides the higher recognition-rate than the existing algorithms using a neural network.

MDPS Analysis Software Development (MDPS 해석 소프트웨어 개발)

  • Jang, Bongchoon;Kim, Joung-Hoon;Yang, Sung-Mo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.9
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    • pp.5480-5486
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    • 2014
  • Complete novel software for MDPS for the simulation and analysis is proposed for steering engineers. The software, MSAS, which can provide the functionality for MDPS Simulation, Analysis & Synthesis, is based on the steering system model, vehicle model and control logic. As the suppliers provide the control logic as a black box, this software is capable of using any type of black box logic or white box control logic that can be developed by logic designers. In addition, this software will be synthesized with the suppliers' s-function control logic and RMDPS together.

A License-Plate Image Binarization Algorithm Based on Least Squares Method for License-Plate Recognition of Automobile Black-Box Image (블랙박스 영상용 자동차 번호판 인식을 위한 최소 자승법 기반의 번호판 영상 이진화 알고리즘)

  • Kim, Jin-young;Lim, Jongtae;Heo, Seo Weon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.5
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    • pp.747-753
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    • 2018
  • In the license-plate recognition systems for automobile black Image, the license-plate image frequently has a shadow due to outdoor environments which are frequently changing. Such a shadow makes unpredictable errors in the segmentation process of individual characters and numbers of the license plate image, and reduces the overall recognition rate. In this paper, to improve the recognition rate in these circumstance, a license-plate image binarization algorithm is proposed removing the shadow effectively. The propose algorithm splits the license-plate image into the regions with the shadow and without. To find out the boundary of two regions, the algorithm estimates the curve for shadow boundary using the least-squares method. The simulation is performed for the license-plate image having its shadow, and the results show much higher recognition rate than the previous algorithm.

Design of Real-time MR Contents using Substitute Videos of Vehicles and Background based on Black Box Video (블랙박스 영상 기반 차량 및 배경 대체 영상을 이용한 실시간 MR 콘텐츠의 설계)

  • Kim, Sung-Ho
    • Journal of Convergence for Information Technology
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    • v.11 no.6
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    • pp.213-218
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    • 2021
  • In this paper, we detect and track vehicles by type based on highway daytime driving videos taken with black boxes for vehicles. In addition, we design a real-time MR contents production method that can be newly created by placing substitute videos of each type of detected vehicles in the same location as the new background video. To detect and track vehicles by type, we use the YOLO algorithm. And we also use the mask technique based on RGB color for substitute videos of each type of vehicles detected. The size of the vehicle substitute videos to be used for MR content are substituted by the same size as the area size of the detected vehicles. In this paper, we confirm that real-time MR contents design is possible as a result of experiments and simulations and believe that It will be usefully utilized in the field of VR contents.

Modeling Framework for Continuous Dynamic Systems Using Machine Learning of Hypothetical Model (가설적 모델의 기계학습을 이용한 연속시간 동적시스템 모델링 프레임워크)

  • Hae Sang Song;Tag Gon Kim
    • Journal of the Korea Society for Simulation
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    • v.32 no.1
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    • pp.13-21
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    • 2023
  • This paper proposes a method of automatically generating a model through a machine learning technique by setting a hypothetical model in the form of a gray box or black box with unknown parameters, when the big data of the actual system is given. We implements the proposed framework and conducts experiments to find an appropriate model among various hypothesis models and compares the cost and fitness of them. As a result we find that the proposed framework works well with continuous systems that could be modeled with ordinary differential equation. This technique is expected to be used well for the purpose of automatically updating the consistency of the digital twin model or predicting the output for new inputs using recently generated big data.

Development of Vehicle Motion Monitoring Module based on Smartphone (스마트폰을 이용한 차량용 주행 모니터링 모듈 개발)

  • Hwang, Jae-Young;Chung, Shin-Il;Chung, Yeon-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.9
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    • pp.1903-1909
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    • 2011
  • This paper presents the development of a core module for integrating data from vehicle by the convergence technology of mobile telematics and black-box. This emerging technology can be referred to as Black-box in Mobile (BIM). For the development of BIM, sensors and cameras were realized in a driving robot. Relevant hardware implementation was achieved to verify the functionality of BIM. The transmitted signal from the driving robot was confirmed in an Android-based portable device. Existing Black-boxes were mostly developed by major transportation companies and focused only on storing data. The proposed BIM offers not only data storage but also easy-to-use real-time monitoring while in motion. In addition, the vehicle can be monitored on parking through shock sensors. This development is considered commercially viable as it is achieved via software implementation.