scholarly journals PENGGUNAAN DRONE UNTUK MENDAPATKAN DATA KECELAKAAN LALU LINTAS

2018 ◽  
Vol 1 (3) ◽  
pp. 147
Author(s):  
Erika Buchari ◽  
Decky Octaviansyah ◽  
Muhammad Taslim Chairuddin ◽  
Lisbeth Dolok Saribu

The awareness of using helmet is still far from the expectation. Often, the motorcycle riders and passengers do not use helmet. It is very dangerous for them and other travelers. However, it is not easy to find and analyze the riders that use or do not use helmet, furthermore to get data of the impact of using or not using helmet in the accident. One of the way to get such data is from “Zebra Operation”. Nowadays, the development of technology of Aerial Photo and geospatial data can be obtained from small format aerial photo. It can be obtained by the means of Unmanned Aerial Vehicle (UAV) with the attached camera on the UAV so that the geospatial data and motor riders without using helmet can be detected. Rider’s behavior can be observed by using UAV or Drone. The aim of this paper is to(1) find the method of observation the travel behavior of riders without using helmet which can endanger other traveler’s safety by using drone (2) find the method of finding the location of accident, type and cause of the accident as quick as possible by using drone. Finding of this paper is a reconstruction method of accident, geometric characteristics of the location, type and cause of the accident as quick as possible. Kesadaran penggunaan helm saat ini masih jauh dari harapan. Seringkali terlihat pengendara sepeda motor dan penumpang yang diboncengnya tidak menggunakan helm. Hal ini sangat membahayakan keselamatannya dan keselamatan banyak orang disekitarnya.Tidak mudah untuk menganalisis jumlah pengguna helm dan pelanggaran lalu lintas, apalagi untuk mengetahui dampak tidak menggunakan helm terhadap korban kecelakaan lalu lintas. Suatu cara termudah untuk mendapatkan data adalah memanfaatkan data dari operasi Zebra. Dengan perkembangan teknologi foto udara, perolehan data permukaan bumi dapat dilakukan dengan menggunakan foto udara format kecil. Foto udara format kecil diperoleh dengan bantuan wahana pesawat udara tanpa awak atau Unmanned Aerial Vehicle dengan meletakkan kamera pada pesawat tersebut sehingga dapat diperoleh data permukaan bumi sesuai dengan yang direncanakan. Perilaku pengendara yang tidak menggunakan helm dan mengabaikan keselamatan diamati dengan menggunakan drone.Tujuan kajian ini adalah untuk:(1) menghasilkan metode pengamatan perilaku pengendara yang tidak menggunakan helm dan yang menyebabkan kecelakaan atau mengabaikan keselamatandengan menggunakan drone,dan (2) menghasilkan metode untuk mendapatkan data kecelakaan, lokasi jenis, dan penyebab kecelakaan secepat mungkin dengan menggunakan drone. Temuan dari paper ini adalah metoda rekonstruksi kecelakaan, karakteristik geometris lokasi, jenis dan penyebab kecelakaan sesegera mungkin.

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yunping Liu ◽  
Xijie Huang ◽  
Yonghong Zhang ◽  
Yukang Zhou

This paper focuses on the dynamic stability analysis of a manipulator mounted on a quadrotor unmanned aerial vehicle, namely, a manipulating unmanned aerial vehicle (MUAV). Manipulator movements and environments interaction will extremely affect the dynamic stability of the MUAV system. So the dynamic stability analysis of the MUAV system is of paramount importance for safety and satisfactory performance. However, the applications of Lyapunov’s stability theory to the MUAV system have been extremely limited, due to the lack of a constructive method available for deriving a Lyapunov function. Thus, Lyapunov exponent method and impedance control are introduced, and the Lyapunov exponent method can establish the quantitative relationships between the manipulator movements and the dynamics stability, while impedance control can reduce the impact of environmental interaction on system stability. Numerical simulation results have demonstrated the effectiveness of the proposed method.


2020 ◽  
Vol 12 (12) ◽  
pp. 2024 ◽  
Author(s):  
Wonkook Kim ◽  
Sunghun Jung ◽  
Yongseon Moon ◽  
Stephen C. Mangum

Multispectral imagery contains abundant spectral information on terrestrial and oceanic targets, and retrieval of the geophysical variables of the targets is possible when the radiometric integrity of the data is secured. Multispectral cameras typically require the registration of individual band images because their lens locations for individual bands are often displaced from each other, thereby generating images of different viewing angles. Although this type of displacement can be corrected through a geometric transformation of the image coordinates, a mismatch or misregistration between the bands still remains, owing to the image acquisition timing that differs by bands. Even a short time difference is critical for the image quality of fast-moving targets, such as water surfaces, and this type of deformation cannot be compensated for with a geometric transformation between the bands. This study proposes a novel morphological band registration technique, based on the quantile matching method, for which the correspondence between the pixels of different bands is not sought by their geometric relationship, but by the radiometric distribution constructed in the vicinity of the pixel. In this study, a Micasense Rededge-M camera was operated on an unmanned aerial vehicle and multispectral images of coastal areas were acquired at various altitudes to examine the performance of the proposed method for different spatial scales. To assess the impact of the correction on a geophysical variable, the performance of the proposed method was evaluated for the chlorophyll-a concentration estimation. The results showed that the proposed method successfully removed the noisy spatial pattern caused by misregistration while maintaining the original spatial resolution for both homogeneous scenes and an episodic scene with a red tide outbreak.


Author(s):  
T. Lendzioch ◽  
J. Langhammer ◽  
M. Jenicek

Airborne digital photogrammetry is undergoing a renaissance. The availability of low-cost Unmanned Aerial Vehicle (UAV) platforms well adopted for digital photography and progress in software development now gives rise to apply this technique to different areas of research. Especially in determining snow depth spatial distributions, where repetitive mapping of cryosphere dynamics is crucial. Here, we introduce UAV-based digital photogrammetry as a rapid and robust approach for evaluating snow accumulation over small local areas (e.g., dead forest, open areas) and to reveal impacts related to changes in forest and snowpack. Due to the advancement of the technique, snow depth of selected study areas such as of healthy forest, disturbed forest, succession, dead forest, and of open areas can be estimated at a 1 cm spatial resolution. The approach is performed in two steps: 1) developing a high resolution Digital Elevation Model during snow-free and 2) during snow-covered conditions. By substracting these two models the snow depth can be accurately retrieved and volumetric changes of snow depth distribution can be achieved. This is a first proof-of-concept study combining snow depth determination and Leaf Area Index (LAI) retrieval to monitor the impact of forest canopy metrics on snow accumulation in coniferous forest within the Šumava National Park, Czech Republic. Both, downward-looking UAV images and upward-looking LAI-2200 canopy analyser measurements were applied to reveal the LAI, controlling interception and transmitting radiation. For the performance of downward-looking images the snow background instead of the sky fraction was used. In contrast to the classical determination of LAI by hemispherical photography or by LAI plant canopy analyser, our approach will also test the accuracy of LAI measurements by UAV that are taken simultaneously during the snow cover mapping campaigns. Since the LAI parameter is important for snowpack modelling, this method presents the potential of simplifying LAI retrieval and mapping of snow dynamics while reducing running costs and time.


2020 ◽  
Vol 47 (3) ◽  
Author(s):  
Олександр Євгенович Волков ◽  
Юрій Петрович Богачук ◽  
Микола Миколайович Комар ◽  
Дмитро Олександрович Волошенюк

Author(s):  
T. Lendzioch ◽  
J. Langhammer ◽  
M. Jenicek

Airborne digital photogrammetry is undergoing a renaissance. The availability of low-cost Unmanned Aerial Vehicle (UAV) platforms well adopted for digital photography and progress in software development now gives rise to apply this technique to different areas of research. Especially in determining snow depth spatial distributions, where repetitive mapping of cryosphere dynamics is crucial. Here, we introduce UAV-based digital photogrammetry as a rapid and robust approach for evaluating snow accumulation over small local areas (e.g., dead forest, open areas) and to reveal impacts related to changes in forest and snowpack. Due to the advancement of the technique, snow depth of selected study areas such as of healthy forest, disturbed forest, succession, dead forest, and of open areas can be estimated at a 1 cm spatial resolution. The approach is performed in two steps: 1) developing a high resolution Digital Elevation Model during snow-free and 2) during snow-covered conditions. By substracting these two models the snow depth can be accurately retrieved and volumetric changes of snow depth distribution can be achieved. This is a first proof-of-concept study combining snow depth determination and Leaf Area Index (LAI) retrieval to monitor the impact of forest canopy metrics on snow accumulation in coniferous forest within the Šumava National Park, Czech Republic. Both, downward-looking UAV images and upward-looking LAI-2200 canopy analyser measurements were applied to reveal the LAI, controlling interception and transmitting radiation. For the performance of downward-looking images the snow background instead of the sky fraction was used. In contrast to the classical determination of LAI by hemispherical photography or by LAI plant canopy analyser, our approach will also test the accuracy of LAI measurements by UAV that are taken simultaneously during the snow cover mapping campaigns. Since the LAI parameter is important for snowpack modelling, this method presents the potential of simplifying LAI retrieval and mapping of snow dynamics while reducing running costs and time.


2019 ◽  
Vol 14 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Kalev Julge ◽  
Artu Ellmann ◽  
Romet Köök

Unmanned aerial vehicle photogrammetry is a surveying technique that enables generating point clouds, 3D surface models and orthophoto mosaics. These are based on photos captured with a camera placed on an unmanned aerial vehicle. Within the framework of this research, unmanned aerial vehicle photogrammetry surveys were carried out over a sand and gravel embankment with the aim of assessing the vertical accuracy of the derived surface models. Flight altitudes, ground control points and cameras were varied, and the impact of various factors on the results was monitored. In addition, the traditional real-time-kinematic Global Navigation Satellite System surveys were conducted for verifications. Surface models acquired by different methods were used to calculate volumes and compare the results with requirements set by Estonian Road Administration. It was found that with proper measuring techniques an accuracy of 5.7 cm for the heights were achieved.


2011 ◽  
Vol 181-182 ◽  
pp. 604-609
Author(s):  
Wei Wan ◽  
Yong Hong Hu ◽  
Peng Wu

For accessing data from different channel in UAV (unmanned aerial vehicle) immediately, a method for massive data and multichannel recorder system is introduced. The system hardware composition and functions are described in details. The software design of receiving program is given, including extended UART ports’ initialization and design of interruption scheme. And experiment result shows that the recorder not only record data from UAV successfully but also improve the way to hand the UAV data.


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