• Title/Summary/Keyword: advanced vehicle

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A Study on the Techniques of Path Planning and Measure of Effectiveness for the SEAD Mission of an UAV (무인기의 SEAD 임무 수행을 위한 임무 경로 생성 및 효과도 산출 기법 연구)

  • Woo, Ji Won;Park, Sang Yun;Nam, Gyeong Rae;Go, Jeong Hwan;Kim, Jae Kyung
    • Journal of Advanced Navigation Technology
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    • v.26 no.5
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    • pp.304-311
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    • 2022
  • Although the SEAD(suppression to enemy air defenses) mission is a strategically important task in modern warfare, the high risk of direct exposure to enemy air defense assets forces to use of unmanned aerial vehicles. this paper proposes a path planning algorithm for SEAD mission for an unmanned aerial vehicle and a method for calculating the mission effectiveness on the planned path. Based on the RRT-based path planning algorithm, a low-altitude ingress/egress flight path that can consider the enemy's short-range air defense threat was generated. The Dubins path-based Intercept path planning technique was used to generate a path that is the shortest path while avoiding the enemy's short-range anti-aircraft threat as much as possible. The ingress/intercept/egress paths were connected in order. In addition, mission effectiveness consisting of fuel consumption, the survival probability, the time required to perform the mission, and the target destruction probability was calculated based on the generated path. The proposed techniques were verified through a scenario.

The Study on Development on LUAV Software based on DO-178 (DO-178 기반 무인비행장치 소프트웨어 개발 방안에 대한 고찰)

  • Ji-hun Kwon;Dong-min Lee;Kyung-min Park;Ye-won Na;Ye-ju Kim;Gi-moung Lee;Jong-whoa Na
    • Journal of Advanced Navigation Technology
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    • v.27 no.4
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    • pp.382-390
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    • 2023
  • The Korea market for LUAV (Light Unmanned Aerial Vehicle) weighing less than 150 kg is growing rapidly. As a result, the market for manufacturing and operating LUAV is expanding, and domestic development of parts and finished products is actively taking place. However, the flight control system and onboard software, which are key components of domestic LUAV, are largely dependent on overseas products due to the excessive cost and period required for development. This paper presented a domestic software development and certification procedure using DO-178C, a guideline for aircraft software development, and the Model-based Development method, and conducted a survey of those involved in the development, manufacturing, and certification of LUAV and analyzed the results. In addition, a case study was conducted to apply the software development plan to the helicopter FCC (Flight Control Computer).

Analysis of the Effect of Learned Image Scale and Season on Accuracy in Vehicle Detection by Mask R-CNN (Mask R-CNN에 의한 자동차 탐지에서 학습 영상 화면 축척과 촬영계절이 정확도에 미치는 영향 분석)

  • Choi, Jooyoung;Won, Taeyeon;Eo, Yang Dam
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.1
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    • pp.15-22
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    • 2022
  • In order to improve the accuracy of the deep learning object detection technique, the effect of magnification rate conditions and seasonal factors on detection accuracy in aerial photographs and drone images was analyzed through experiments. Among the deep learning object detection techniques, Mask R-CNN, which shows fast learning speed and high accuracy, was used to detect the vehicle to be detected in pixel units. Through Seoul's aerial photo service, learning images were captured at different screen magnifications, and the accuracy was analyzed by learning each. According to the experimental results, the higher the magnification level, the higher the mAP average to 60%, 67%, and 75%. When the magnification rates of train and test data of the data set were alternately arranged, low magnification data was arranged as train data, and high magnification data was arranged as test data, showing a difference of more than 20% compared to the opposite case. And in the case of drone images with a seasonal difference with a time difference of 4 months, the results of learning the image data at the same period showed high accuracy with an average of 93%, confirming that seasonal differences also affect learning.

Methodology of Test for sUAV Navigation System Error (소형무인항공기 항법시스템오차 시험평가 방법)

  • SungKwan Ku;HyoJung Ahn;Yo-han Ju;Seokmin Hong
    • Journal of Advanced Navigation Technology
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    • v.25 no.6
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    • pp.510-516
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    • 2021
  • Recently, the range of utilization and demand for unmanned aerial vehicle (UAV) has been continuously increasing, and research on the construction of a separate operating system for low-altitude UAV is underway through the development of a management system separate from manned aircraft. Since low-altitude UAVs also fly in the airspace, it is essential to establish technical standards and certification systems necessary for the operation of the aircraft, and research on this is also in progress. If the operating standards and certification requirements of the aircraft are presented, a test method to confirm this should also be presented. In particular, the accuracy of small UAV's navigation required during flight is required to be more precise than that of a manned aircraft or a large UAV. It was necessary to calculate a separate navigation error. In this study, we presented a test method for deriving navigation errors that can be applied to UAVs that have difficulty in acquiring long-term operational data, which is different from existing manned aircraft, and conducted verification tests.

Thermal Imaging Camera Development for Automobiles using Detail Enhancement Technique (디테일 향상 기법을 적용한 자동차용 열상카메라 개발)

  • Cho, Deog-Sang;Yang, In-Beom
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.3
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    • pp.687-692
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    • 2018
  • In this paper, the development of an automotive thermal imaging camera providing image information for ADAS (Advanced Driver Assist System) and autonomous vehicles is described and an improved technique to enhance the details of the image is proposed. Thermal imaging cameras are used in various fields, such as the medical, industrial and military fields, for the purpose of temperature measurement and night vision. In automobiles, they are utilized for night vision systems. For their utilization in ADAS and autonomous vehicles, appropriate image resolution and enhanced detail are required for object recognition. In this study, a $640{\times}480$ resolution thermal imaging camera that can be applied to automobiles is developed and the BDE (Block-Range Detail Enhancement) technique is applied to improve the details of the image. In order to improve the image detail obtained in various driving environments, the block-range values between the target pixel and the surrounding 8 pixels are calculated and classified into 5 levels. Then, different factors are added or subtracted to obtain images with high utilization. The improved technique distinguishes the dark part of the image by the resulting temperature difference of 130mK and shows an improvement in the fine detail in both the bright and dark parts of the image. The developed thermal imaging camera using the improved detail enhancement technique is applied to a test vehicle and the results are presented.

Empennage Design of Solar-Electric Powered High Altitude Long Endurance Unmanned Aerial Vehicle (고고도 장기체공 전기 동력 무인기의 꼬리 날개 설계)

  • Hwang, Seung-Jae;Lee, Yung-Gyo;Kim, Cheol-Wan;Ahn, Seok-Min
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.41 no.9
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    • pp.708-713
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    • 2013
  • KARI is developing a solar-electric powered HALE UAV(EAV-3). For demonstrating the technology, EAV-2H, a down-scaled version of EAV-3, is developed and after EAV-2H's initial flight test, the directional stability and control need to be improved. Thus, the vertical tail and rudder of EAV-2H are redesigned with Advanced Aircraft Analysis(AAA). Size of the rudder is increased from mean chord ratio of rudder to vertical tail, $C_r/C_v(%)=30$ to $C_r/C_v(%)=60$ and size of the vertical tail is reduced 15%. As a result, the directional control to side wind($v_1$) is improved to sideslip angle, ${\beta}(deg)=25^{\circ}$ and $v_1(m/sec)=3.54$. Also, variation of airplane side force coefficient with sideslip angle ($C_{y_{\beta}}$) and variation of airplane side force coefficient with dimensionless rate of change of yaw rate ($C_{y_r}$) are reduced 15% and 22%, respectively to minimize the effect of side wind. The empennage design of EAV-2H is verified with flight tests and applied to design of KARI's solar-electric-powered EAV-3.

Verification of Navigation System of Guided Munition by Flight Experiment (비행 실험을 통한 유도형 탄약 항법 시스템 검증)

  • Kim, Youngjoo;Lim, Seunghan;Bang, Hyochoong;Kim, Jaeho;Pak, Changho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.44 no.11
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    • pp.965-972
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    • 2016
  • This paper presents results of flight experiments on a navigation algorithm including multiplicative extended Kalman filter for estimating attitude of the guided munition. The filter describes orientation of aircraft by data fusion with low-cost sensors where measurement update is done by multiplication, rather than addition, which is suitable for quaternion representation. In determining attitude from vector observations, the existing approach utilizes a 3-axis accelerometer as a 2-axis inclinometer by measuring gravity to estimate pitch and roll angles, while GNSS velocity is used to derive heading of the vehicle. However, during accelerated maneuvers such as coordinated flight, the accelerometer provides inadequate inclinometer measurements. In this paper, the measurement update process is newly defined to complement the vulnerability by using different vector observations. The acceleration measurement is considered as a result of a centrifugal force and gravity during turning maneuvers and used to estimate roll angle. The effectiveness of the proposed method is verified through flight experiments.

A Study on Network Based Traffic Signal Optimization Using Traffic Prediction Data (교통예측자료 기반 Network 차원의 신호제어 최적화 방안)

  • Han, Jeong-hye;Lee, Seon-Ha;Cheon, Choon-Keun;Oh, Tae-ho;Kim, Eun-Ji
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.14 no.6
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    • pp.77-90
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    • 2015
  • An increasing number of vehicles is causing various traffic problems such as chronic congestion of highways and air pollution. Local governments have been managing traffic by constructing systems such as Intelligent Transport Systems (ITS) and Advanced Traffic Management Systems (ATMS) to relieve such problems, but construction of an infrastructure-based traffic system is insufficient in resolving chronic traffic problems. A more sophisticated system with enhanced operational management capabilities added to the existing facilities is necessary at this point. As traffic patterns of the urban traffic flow is time-specific due to the different vehicle populations throughout the time of the day, a local network-wide signal operation plan that can manage such situation-specific traffic patterns is deemed to be necessary. Therefore, this study is conducted for the purpose of establishment of a plan for contextual signal control management through signal optimization at the network level after setting the Frame Signal in accordance to the traffic patterns gathered from the short-term traffic forecast data as a means to mitigate the problems with existing standardized signal operations.

Automated Vehicle Research by Recognizing Maneuvering Modes using LSTM Model (LSTM 모델 기반 주행 모드 인식을 통한 자율 주행에 관한 연구)

  • Kim, Eunhui;Oh, Alice
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.4
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    • pp.153-163
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    • 2017
  • This research is based on the previous research that personally preferred safe distance, rotating angle and speed are differentiated. Thus, we use machine learning model for recognizing maneuvering modes trained per personal or per similar driving pattern groups, and we evaluate automatic driving according to maneuvering modes. By utilizing driving knowledge, we subdivided 8 kinds of longitudinal modes and 4 kinds of lateral modes, and by combining the longitudinal and lateral modes, we build 21 kinds of maneuvering modes. we train the labeled data set per time stamp through RNN, LSTM and Bi-LSTM models by the trips of drivers, which are supervised deep learning models, and evaluate the maneuvering modes of automatic driving for the test data set. The evaluation dataset is aggregated of living trips of 3,000 populations by VTTI in USA for 3 years and we use 1500 trips of 22 people and training, validation and test dataset ratio is 80%, 10% and 10%, respectively. For recognizing longitudinal 8 kinds of maneuvering modes, RNN achieves better accuracy compared to LSTM, Bi-LSTM. However, Bi-LSTM improves the accuracy in recognizing 21 kinds of longitudinal and lateral maneuvering modes in comparison with RNN and LSTM as 1.54% and 0.47%, respectively.

The Analysis of Bus Traffic Accident to Support Safe Driving for Bus Drivers (버스운전자 안전운행지원을 위한 교통사고 분석 연구)

  • BHIN, Miyoung;SON, Seulki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.1
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    • pp.14-26
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    • 2019
  • For bus drivers' safe driving, a policy that analyzes the causes of the drivers' traffic accidents and then assists their safe driving is required. Therefore, the Ministry of Land, Infrastructure and Transport set up its plan to gradually expand the equipping of commercial vehicles with FCWS (Forward Collision Warning System) and LDWS(Lane Departure Warning System), from the driver-supporting ADAS(Advanced Driver Assistance Systems). However, there is not much basic research on the analysis of bus drivers' traffic accidents in Korea. As such, the time is appropriate to research what is the most necessary ADAS for bus drivers going forward to prevent bus accidents. The purpose of this research is to analyze how serious the accidents were in the different bus routes and whether the accidents were repetitive, and to give recommendations on how to support ADAS for buses, as an improvement. A model of ordered logit was used to analyze how serious the accidents were and as a result, vehicle to pedestrian accidents which directly affected individuals were statistically significant in all of the models, and violations of regulations, such as speeding, traffic signal violation and violation of safeguards for passengers, were indicated in common in several models. Therefore, the pedestrian-sensor system and automatic emergency control device for pedestrian should be installed to reduce bus accidents directly affecting persons in the future, and education for drivers and ADAS are to be offered to reduce the violations of regulations.