• Title/Summary/Keyword: HD Map

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Method to Improve Localization and Mapping Accuracy on the Urban Road Using GPS, Monocular Camera and HD Map (GPS와 단안카메라, HD Map을 이용한 도심 도로상에서의 위치측정 및 맵핑 정확도 향상 방안)

  • Kim, Young-Hun;Kim, Jae-Myeong;Kim, Gi-Chang;Choi, Yun-Soo
    • Korean Journal of Remote Sensing
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    • v.37 no.5_1
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    • pp.1095-1109
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    • 2021
  • The technology used to recognize the location and surroundings of autonomous vehicles is called SLAM. SLAM standsfor Simultaneously Localization and Mapping and hasrecently been actively utilized in research on autonomous vehicles,starting with robotic research. Expensive GPS, INS, LiDAR, RADAR, and Wheel Odometry allow precise magnetic positioning and mapping in centimeters. However, if it can secure similar accuracy as using cheaper Cameras and GPS data, it will contribute to advancing the era of autonomous driving. In this paper, we present a method for converging monocular camera with RTK-enabled GPS data to perform RMSE 33.7 cm localization and mapping on the urban road.

Overexpression of Protein Kinase $C{\beta}_1$ Restores Mitogenic Responses of Enterocytic Differentiated Colon Carcinoma Cells to Diacylglycerol and Basic FGF

  • Lee, Han-Soo
    • BMB Reports
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    • v.30 no.3
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    • pp.194-199
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    • 1997
  • Previous studies have shown that the HD3 human enterocytic differentiated colon carcinoma cell lines having low $PKC{\beta}$ activity did not respond to diacylglycerol and basic FGF by growth and by activation of pp57 MAP kinase, but undifferentiated cell lines exhibiting high $PKC{\beta}$ activity did. To confirm a role of $PKC{\beta}$ in colonocyte mitogenesis, derivatives of HD3 cell line that stably overexpress a full-length of cDNA encoding the ${\beta}_1$ isoform of human PKC were generated. The abundance and activity of $PKC{\beta}$ in two of the these cell lines, PKC3 and PKC8 were much higher than those in the C1 control cell line that carries the vector lacking the $PKC{\beta}_1\;cDNA$ insert. Following exposure to diacylglycerol or basic FGF, proliferation of PKC3 and PKC8 cells increased about 50%; but this effect was not seen with the control C1 cells. Also, in contrast to the control cells, the $PKC{\beta}_1-overproducing$ cells displayed activation of pp57 MAP kinase when treated with diacylglycerol and basic FGF as undifferentiated cell lines did. These results provide direct evidence that $PKC{\beta}_1$ which plays a key role in mitogenic responses of colon carcinoma cells to diacylglycerol and basic FGF is down-regulated in enterocytic differentiation of colon cells.

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Prevalence and Significance of Immature Ganglion Cell in Hirschsprung's Disease (히르슈슈프룽병 환자에서 미성숙 신경절 세포의 빈도 및 그 의의)

  • Yang, Hee-Beom;Kim, Hyun-Young;Kim, Soo-Hong;Jung, Sung-Eun;Park, Kwi-Won
    • Advances in pediatric surgery
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    • v.19 no.2
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    • pp.122-129
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    • 2013
  • Immature ganglion cell (IGC) is known for its relationship with intestinal motility and its impact on postoperative functional outcomes of Hirschsprung's disease (HD). There are few studies on the relationship between intestinal dysmotility and IGC in HD patients. 67 patients pathologically diagnosed with HD and who received definitive operation in Seoul National University Children's Hospital from 2010 to 2011 were included. 10 patients were excluded due to inadequate immunohistochemical staining results. The proximal end of resected ganglionic segment was evaluated with immunohistochemistry examination with MAP-2, a marker of ganglionic cells and bcl-2, a marker of IGCs The median age at operation was 155 (15-4678) day-old. 55 (96.5%) patients positive for bcl-2, were regarded as having IGC, and 2 (3.5%) patients positive for MAP-2 but negative for bcl-2, were regarded as having only mature ganglion cells. In the bcl-2 positive group, there were 7 patients (12.7%) with constipation, 15 patients (27.3%) with soiling, 3 patients (5.5%) with perianal excoriation and 6 patients (10.9%) with medication use. In bcl-2 negative group, intestinal dysmotility was not seen. There was no statistical significance in the two groups. Considering that HD is diagnosed at a young age, the rate of IGC present is very high and it might be inappropriate to relate IGC to functional outcome at young ages.

Development of Multi-Camera based Mobile Mapping System for HD Map Production (정밀지도 구축을 위한 다중카메라기반 모바일매핑시스템 개발)

  • Hong, Ju Seok;Shin, Jin Soo;Shin, Dae Man
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.6
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    • pp.587-598
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    • 2021
  • This study aims to develop a multi-camera based MMS (Mobile Mapping System) technology for building a HD (High Definition) map for autonomous driving and for quick update. To replace expensive lidar sensors and reduce long processing times, we intend to develop a low-cost and efficient MMS by applying multiple cameras and real-time data pre-processing. To this end, multi-camera storage technology development, multi-camera time synchronization technology development, and MMS prototype development were performed. We developed a storage module for real-time JPG compression of high-speed images acquired from multiple cameras, and developed an event signal and GNSS (Global Navigation Satellite System) time server-based synchronization method to record the exposure time multiple images taken in real time. And based on the requirements of each sector, MMS was designed and prototypes were produced. Finally, to verify the performance of the manufactured multi-camera-based MMS, data were acquired from an actual 1,000 km road and quantitative evaluation was performed. As a result of the evaluation, the time synchronization performance was less than 1/1000 second, and the position accuracy of the point cloud obtained through SFM (Structure from Motion) image processing was around 5 cm. Through the evaluation results, it was found that the multi-camera based MMS technology developed in this study showed the performance that satisfies the criteria for building a HD map.

A Study on Real-time Autonomous Driving Simulation System Construction based on Digital Twin - Focused on Busan EDC - (디지털트윈 기반 실시간 자율주행 시뮬레이션 시스템 구축 방안 연구 - 부산 EDC 중심으로 -)

  • Kim, Min-Soo;Park, Jong-Hyun;Sim, Min-Seok
    • Journal of Cadastre & Land InformatiX
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    • v.53 no.2
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    • pp.53-66
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    • 2023
  • Recently, there has been a significant interest in the development of autonomous driving simulation environment based on digital twin. In the development of such digital twin-based simulation environment, many researches has been conducted not only performance and functionality validation of autonomous driving, but also generation of virtual training data for deep learning. However, such digital twin-based autonomous driving simulation system has the problem of requiring a significant amount of time and cost for the system development and the data construction. Therefore, in this research, we aim to propose a method for rapidly designing and implementing a digital twin-based autonomous driving simulation system, using only the existing 3D models and high-definition map. Specifically, we propose a method for integrating 3D model of FBX and NGII HD Map for the Busan EDC area into CARLA, and a method for adding and modifying CARLA functions. The results of this research show that it is possible to rapidly design and implement the simulation system at a low cost by using the existing 3D models and NGII HD map. Also, the results show that our system can support various functions such as simulation scenario configuration, user-defined driving, and real-time simulation of traffic light states. We expect that usability of the system will be significantly improved when it is applied to broader geographical area in the future.

Accelerating the Retinex Algorithm with CUDA

  • Seo, Hyo-Seok;Kwon, Oh-Young
    • Journal of information and communication convergence engineering
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    • v.8 no.3
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    • pp.323-327
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    • 2010
  • Recently, the television market trend is change to HD television and the need of the study on HD image enhancement is increased rapidly. To enhancement of image quality, the retinex algorithm is commonly used. That's why we studied how to accelerate the retinex algorithm with CUDA on GPGPU (general purpose graphics processing unit). Calculating average part in retinex algorithm is similar to pyramidal calculation. We parallelize this recursive pyramidal average calculating for all layers, map the average data into the 2D plane and reduce the calculating time dramatically. Sequential C code takes 8948ms to get the average values for all layers in $1024{\times}1024$ image, but proposed method takes only only about 0.9ms for the same image. We are going to study about the real-time HD video rendering and image enhancement.

Study on Applying New Infrastructure for Autonomous Driving in HD Maps (자율주행을 위한 인프라의 정밀도로지도 적용 방안 연구)

  • Young-Jae JEON;Chul-Woo PARK;Sang-Yeon WON;Jun-Hyuk LEE
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.4
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    • pp.116-129
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    • 2023
  • Recently, interest in autonomous driving has drawn attention to autonomous cooperative driving, which considers the development of driving technology of autonomous vehicles and the development of infrastructure that constitutes a driving environment. According to the concept of autonomous cooperative driving, This study analyzes the new infrastructure for autonomous driving that can complement the information of existing precise road maps and adding HD map layer as the new infrastructure. The new infrastructure for autonomous driving presented two types of improved facilities and one type of sensor only facility. Analysis of HD maps shows that information such as junction points rarely changes, but it is expected that infrastructure for autonomous driving can be added to convey the meaning of paying attention to obstacles that may arise at the junction. In this way, the new infrastructure for autonomous driving needs to support the roles of guidance, instruction, and attention that existing road facilities.

Molecular Cloning of nifHD from Rhizobium sp. SNU003 (Rhizobium sp. SNU003의 nifHD 클로닝)

  • 강명수;안정선
    • Korean Journal of Microbiology
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    • v.31 no.2
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    • pp.123-128
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    • 1993
  • Genes for dinitrogenase reductase (nifH) and dinitogenase a subunit (nifD) were found to be located on 7.9 kb of EcoRI, 6.5 kb of Sail, 7.3 kb of HindlII and 4.4 kb of Pstl fragments of the genomic blot of Rhizobium sp. SNU003. a symbiotic strain from root nodule of Canavalia lineata. Nine recombinant phage nif-clones were selected from the genomic library constructed by using EMBL-3 BamHI arms of bacteriophage lambda. Among them. Rnif-6 had insert DNA of 15.3 kb. in which 7.6 kb of BamHI!SacI fragment contained nifHD region. Therefore, the 7.6 kb fragment was subcloned into pUC19 and partial restriction map was constructed. As the results, nifH and nifD were found to be located continuously on 4.5 kb of BamHI/BglIl in the genome of Rhizobium sp. SNU003 strain.

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BIPRODUCT BIALGEBRAS WITH A PROJECTION ONTO A HOPF ALGEBRA

  • Park, Junseok
    • Journal of the Chungcheong Mathematical Society
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    • v.26 no.1
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    • pp.91-103
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    • 2013
  • Let (D,B) be an admissible pair. Then recall that $B\;{\times}^L_HD^{{\rightarrow}{\pi}_D}_{{\leftarrow}i_D}\;D$ are bialgebra maps satisfying ${\pi}_D{\circ}i_D=I$. We have solved a converse in case D is a Hopf algebra. Let D be a Hopf algebra with antipode $S_D$ and be a left H-comodule algebra and a left H-module coalgebra over a field $k$. Let A be a bialgebra over $k$. Suppose $A^{{\rightarrow}{\pi}}_{{\leftarrow}i}D$ are bialgebra maps satisfying ${\pi}{\circ}i=I_D$. Set ${\Pi}=I_D*(i{\circ}s_D{\circ}{\pi}),B=\Pi(A)$ and $j:B{\rightarrow}A$ be the inclusion. Suppose that ${\Pi}$ is an algebra map. We show that (D,B) is an admissible pair and $B^{\leftarrow{\Pi}}_{\rightarrow{j}}A^{\rightarrow{\pi}}_{\leftarrow{i}}D$ is an admissible mapping system and that the generalized biproduct bialgebra $B{\times}^L_HD$ is isomorphic to A as bialgebras.

Machine Learning Based MMS Point Cloud Semantic Segmentation (머신러닝 기반 MMS Point Cloud 의미론적 분할)

  • Bae, Jaegu;Seo, Dongju;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.939-951
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    • 2022
  • The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.