• Title/Summary/Keyword: Vehicle sensing data

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Construction of Coastal Surveying Database and Application Using Drone

  • Park, Joon Kyu;Lee, Keun Wang
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.3
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    • pp.197-202
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    • 2018
  • Drone has been continuously studied in the field of geography and remote sensing. The basic researches have been actively carried out before the utilization in the field of photogrammetry. In Korea, it is necessary to study the actual way of research in accordance with the drone utilization environment. In particular, analysis on the characteristics of DSM (Digital Surface Model) generated through drone are needed. In this study, the characteristic of drone DSM as a data acquisition method was analyzed for coastal management. The coastal area was selected as the study area, and data was acquired by using drone. As a result of the study, the terrain model and the ortho image of coastal area were produced. The accuracy of UAV (Unmanned Aerial Vehicle) results were very high about 10cm at check points. However, concavo-convex shapes appeared in very flat areas such as tidal flats and roads. To correct this terrain model distortion, a new terrain model was created through data processing and the results were evaluated. If additional studies are carried out and the construction and analysis of terrain model using drone image is done, drone data for coastal management will be available.

3D Measurement Method Based on Point Cloud and Solid Model for Urban SingleTrees (Point cloud와 solid model을 기반으로 한 단일수목 입체적 정량화기법 연구)

  • Park, Haekyung
    • Korean Journal of Remote Sensing
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    • v.33 no.6_2
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    • pp.1139-1149
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    • 2017
  • Measuring tree's volume is very important input data of various environmental analysis modeling However, It's difficult to use economical and equipment to measure a fragmented small green space in the city. In addition, Trees are sensitive to seasons, so we need new and easier equipment and quantification methods for measuring trees than lidar for high frequency monitoring. In particular, the tree's size in a city affect management costs, ecosystem services, safety, and so need to be managed and informed on the individual tree-based. In this study, we aim to acquire image data with UAV(Unmanned Aerial Vehicle), which can be operated at low cost and frequently, and quickly and easily quantify a single tree using SfM-MVS(Structure from Motion-Multi View Stereo), and we evaluate the impact of reducing number of images on the point density of point clouds generated from SfM-MVS and the quantification of single trees. Also, We used the Watertight model to estimate the volume of a single tree and to shape it into a 3D structure and compare it with the quantification results of 3 different type of 3D models. The results of the analysis show that UAV, SfM-MVS and solid model can quantify and shape a single tree with low cost and high time resolution easily. This study is only for a single tree, Therefore, in order to apply it to a larger scale, it is necessary to follow up research to develop it, such as convergence with various spatial information data, improvement of quantification technique and flight plan for enlarging green space.

Comparison of Deep Learning-based Unsupervised Domain Adaptation Models for Crop Classification (작물 분류를 위한 딥러닝 기반 비지도 도메인 적응 모델 비교)

  • Kwak, Geun-Ho;Park, No-Wook
    • Korean Journal of Remote Sensing
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    • v.38 no.2
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    • pp.199-213
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    • 2022
  • The unsupervised domain adaptation can solve the impractical issue of repeatedly collecting high-quality training data every year for annual crop classification. This study evaluates the applicability of deep learning-based unsupervised domain adaptation models for crop classification. Three unsupervised domain adaptation models including a deep adaptation network (DAN), a deep reconstruction-classification network, and a domain adversarial neural network (DANN) are quantitatively compared via a crop classification experiment using unmanned aerial vehicle images in Hapcheon-gun and Changnyeong-gun, the major garlic and onion cultivation areas in Korea. As source baseline and target baseline models, convolutional neural networks (CNNs) are additionally applied to evaluate the classification performance of the unsupervised domain adaptation models. The three unsupervised domain adaptation models outperformed the source baseline CNN, but the different classification performances were observed depending on the degree of inconsistency between data distributions in source and target images. The classification accuracy of DAN was higher than that of the other two models when the inconsistency between source and target images was low, whereas DANN has the best classification performance when the inconsistency between source and target images was high. Therefore, the extent to which data distributions of the source and target images match should be considered to select the best unsupervised domain adaptation model to generate reliable classification results.

LOS (Line of Sight) Algorithm and Unknown Input Observer Based Leader-Follower Formation Control (LOS 알고리듬과 미지 입력 관측기에 기초한 선도-추종 대형 제어)

  • Yoon, Suk-Min;Yeu, Tae-Kyeong;Park, Seong-Jea;Hong, Sup;Kim, Sang-Bong
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.3
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    • pp.207-214
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    • 2010
  • This paper proposes about decentralized control approach based Leader-Follower formation control using LOS (Line of Sight) algorithm and unknown input observer. The position of robots which is a basic information in multi-robot or single robot motion control is determined by localization algorithm fusing UPS (Ultrasonic Position System) and kinematics model. For formation control, a decentralized control approach individually installing a local controller in leader and follower robot is adopted. Leader robot is controlled to track a specified trajectory by LOS algorithm, and the other robots follow the leader by local controller based on tracking platoon level function, self-sensing data and estimated information from unknown input observer. The performance of proposed method is proven through the formation experiment of two vehicle models.

Structural Damage Localization for Visual Inspection Using Unmanned Aerial Vehicle with Building Information Modeling Information (UAV와 BIM 정보를 활용한 시설물 외관 손상의 위치 측정 방법)

  • Lee, Yong-Ju;Park, Man-Woo
    • Journal of KIBIM
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    • v.13 no.4
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    • pp.64-73
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    • 2023
  • This study introduces a method of estimating the 3D coordinates of structural damage from the detection results of visual inspection provided in 2D image coordinates using sensing data of UAV and 3D shape information of BIM. This estimation process takes place in a virtual space and utilizes the BIM model, so it is possible to immediately identify which member of the structure the estimated location corresponds to. Difference from conventional structural damage localization methods that require 3D scanning or additional sensor attachment, it is a method that can be applied locally and rapidly. Measurement accuracy was calculated through the distance difference between the measured position measured by TLS (Terrestrial Laser Scanner) and the estimated position calculated by the method proposed in this study, which can determine the applicability of this study and the direction of future research.

Study on Advisory Safety Speed Model Using Real-time Vehicular Data (실시간 차량정보를 이용한 안전권고속도 산정방안에 관한 연구)

  • Jang, JeongAh;Kim, HyunSuk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.5D
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    • pp.443-451
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    • 2010
  • This paper proposes the methodology about advisory safety speed based on real-time vehicular data collected from highway. The proposed model is useful information to drivers by appling seamless wireless communication and being collected from ECU(Engine Control Unit) equipment in every vehicle. Furthermore, this model also permits the use of realtime sensing data like as adverse weather and road-surface data. Here, the advisory safety speed is defined "the safety speed for drivers considering the time-dependent traffic condition and road-surface state parameter at uniform section", and the advisory safety speed model is developed by considering the parameters: inter-vehicles safe stopping distance, statistical vehicle speed, and real-time road-surface data. This model is evaluated by using the simulation technique for exploring the relationships between advisory safety speed and the dependent parameters like as traffic parameters(smooth condition and traffic jam), incident parameters(no-accident and accident) and road-surface parameters(dry, wet, snow). A simulation's results based on 12 scenarios show significant relationships and trends between 3 parameters and advisory safety speed. This model suggests that the advisory safety speed has more higher than average travel speed and is changeable by changing real-time incident states and road-surface states. The purpose of the research is to prove the new safety related services which are applicable in SMART Highway as traffic and IT convergence technology.

Implementation of Wireless Automatic Control System for Vehicle Interior Environment (차량 내부 환경 제어용 무선 자동화 시스템 구현)

  • Cho, Hae-Seong;Cho, Ju-Phil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.5
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    • pp.287-291
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    • 2010
  • In this paper, we designed and implemented mobile object automatic system based on senor networks for telematics. For developing this system, we gather the various sensing data through wireless communication method using zigbee sensor networks and analyze them in monitoring equipment. And we enable the driver to recognize the car state information on the whole by interfacing analyzed data to telematics unit. And, we implemented automatic controller that can control temperature and humidity in car automatically by actuating air conditioner based on the data that was monitored throughout temperature sensor, humidity sensor and brightness sensor based on sensor networks.

3-D Hetero-Integration Technologies for Multifunctional Convergence Systems

  • Lee, Kang-Wook
    • Journal of the Microelectronics and Packaging Society
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    • v.22 no.2
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    • pp.11-19
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    • 2015
  • Since CMOS device scaling has stalled, three-dimensional (3-D) integration allows extending Moore's law to ever high density, higher functionality, higher performance, and more diversed materials and devices to be integrated with lower cost. 3-D integration has many benefits such as increased multi-functionality, increased performance, increased data bandwidth, reduced power, small form factor, reduced packaging volume, because it vertically stacks multiple materials, technologies, and functional components such as processor, memory, sensors, logic, analog, and power ICs into one stacked chip. Anticipated applications start with memory, handheld devices, and high-performance computers and especially extend to multifunctional convengence systems such as cloud networking for internet of things, exascale computing for big data server, electrical vehicle system for future automotive, radioactivity safety system, energy harvesting system and, wireless implantable medical system by flexible heterogeneous integrations involving CMOS, MEMS, sensors and photonic circuits. However, heterogeneous integration of different functional devices has many technical challenges owing to various types of size, thickness, and substrate of different functional devices, because they were fabricated by different technologies. This paper describes new 3-D heterogeneous integration technologies of chip self-assembling stacking and 3-D heterogeneous opto-electronics integration, backside TSV fabrication developed by Tohoku University for multifunctional convergence systems. The paper introduce a high speed sensing, highly parallel processing image sensor system comprising a 3-D stacked image sensor with extremely fast signal sensing and processing speed and a 3-D stacked microprocessor with a self-test and self-repair function for autonomous driving assist fabricated by 3-D heterogeneous integration technologies.

A Study on Improvement of Crash Discrimination Performance for Offset and Angular Crash Events Using Electronic X-Y 2-Axis Accelerometer (전자식 X-Y 이축 가속도 센서를 이용한 오프셋 및 경사 충돌에 대한 충돌 판별 성능 개선에 관한 연구)

  • 박서욱;전만철
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.1
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    • pp.128-136
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    • 2003
  • In today's design trend of vehicle structure, crush zone is fiequently reinforced by adding a box-shaped sub-frame in order to avoid an excessive deformation against a high-speed offset barrier such as EU Directive 96/97 EC, IIHS offset test. That kind of vehicle structure design results in a relatively monotonic crash pulse for airbag ECU(Electronic Control Unit) located at non-crush zone. As for an angular crash event, the measured crash signal using a single-axis accelerometer in a longitudinal direction is usually weaker than that of frontal barrier crash. Therefore, it is not so easy task to achieve a satisfactory crash discrimination performance for offset and angular crash events. In this paper, we introduce a new crash discrimination algorithm using an electronic X-Y 2-axis accelerometer in order to improve crash discrimination performance especially for those crash events. The proposed method uses a crash signal in lateral direction(Y-axis) as well as in longitudinal direction(X-axis). A crash severity measure obtained from Y-axis acceleration is used to improve the discrimination between fire and no-fire events. The result obtained by the proposed measure is logically ORed with an existing algorithm block using X-axis crash signal. Simulation and pulse injection test have been conducted to verify the performance of proposed algorithm by using real crash data of a 2,000cc passenger vehicle.

Retrieval and Validation of Precipitable Water Vapor using GPS Datasets of Mobile Observation Vehicle on the Eastern Coast of Korea

  • Kim, Yoo-Jun;Kim, Seon-Jeong;Kim, Geon-Tae;Choi, Byoung-Choel;Shim, Jae-Kwan;Kim, Byung-Gon
    • Korean Journal of Remote Sensing
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    • v.32 no.4
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    • pp.365-382
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    • 2016
  • The results from the Global Positioning System (GPS) measurements of the Mobile Observation Vehicle (MOVE) on the eastern coast of Korea have been compared with REFerence (REF) values from the fixed GPS sites to assess the performance of Precipitable Water Vapor (PWV) retrievals in a kinematic environment. MOVE-PWV retrievals had comparatively similar trends and fairly good agreements with REF-PWV with a Root-Mean-Square Error (RMSE) of 7.4 mm and $R^2$ of 0.61, indicating statistical significance with a p-value of 0.01. PWV retrievals from the June cases showed better agreement than those of the other month cases, with a mean bias of 2.1 mm and RMSE of 3.8 mm. We further investigated the relationships of the determinant factors of GPS signals with the PWV retrievals for detailed error analysis. As a result, both MultiPath (MP) errors of L1 and L2 pseudo-range had the best indices for the June cases, 0.75-0.99 m. We also found that both Position Dilution Of Precision (PDOP) and Signal to Noise Ratio (SNR) values in the June cases were better than those in other cases. That is, the analytical results of the key factors such as MP errors, PDOP, and SNR that can affect GPS signals should be considered for obtaining more stable performance. The data of MOVE can be used to provide water vapor information with high spatial and temporal resolutions in the case of dramatic changes of severe weather such as those frequently occurring in the Korean Peninsula.