• Title/Summary/Keyword: Autonomous driving

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Analysis of the Effects of the Truck Platooning Using a Meta-analysis (메타분석을 이용한 화물차 군집주행의 효과 분석)

  • Kim, Yejin;Jeong, Harim;Ko, Woori;Park, Joong-gyu;Yun, Ilsoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.1
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    • pp.76-90
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    • 2022
  • The platooning refers to a form in which one or more following vehicles along the path of the leading vehicle(directly driven by the driver) drive in one platoon using V2V, V2I communication and vehicle-mounted sensor. Platooning has emerged in line with the increasing demand for cargo volume and advanced transportation logistics systems, and is expected to have effects such as increasing capacity, reducing labor costs, and reducing fuel consumption. However, compared to general passenger cars, research on autonomous driving of trucks and verification of their effects are insufficient. Therefore, in this study, meta-analysis was conducted on the theme of the effect of truck platooning, and the results of existing studies related to platooning effects were integrated into one reliable, generalized, and objective summary estimate. In conclusion, it was analyzed that the introduction of truck platooning would have an effect of 13.93% increase in capacity, 38.76% decrease in conflict, and 8.13% decrease in fuel consumption.

Predicting Unseen Object Pose with an Adaptive Depth Estimator (적응형 깊이 추정기를 이용한 미지 물체의 자세 예측)

  • Sungho, Song;Incheol, Kim
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.12
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    • pp.509-516
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    • 2022
  • Accurate pose prediction of objects in 3D space is an important visual recognition technique widely used in many applications such as scene understanding in both indoor and outdoor environments, robotic object manipulation, autonomous driving, and augmented reality. Most previous works for object pose estimation have the limitation that they require an exact 3D CAD model for each object. Unlike such previous works, this paper proposes a novel neural network model that can predict the poses of unknown objects based on only their RGB color images without the corresponding 3D CAD models. The proposed model can obtain depth maps required for unknown object pose prediction by using an adaptive depth estimator, AdaBins,. In this paper, we evaluate the usefulness and the performance of the proposed model through experiments using benchmark datasets.

Panorama Image Stitching Using Sythetic Fisheye Image (Synthetic fisheye 이미지를 이용한 360° 파노라마 이미지 스티칭)

  • Kweon, Hyeok-Joon;Cho, Donghyeon
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.20-30
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    • 2022
  • Recently, as VR (Virtual Reality) technology has been in the spotlight, 360° panoramic images that can view lively VR contents are attracting a lot of attention. Image stitching technology is a major technology for producing 360° panorama images, and many studies are being actively conducted. Typical stitching algorithms are based on feature point-based image stitching. However, conventional feature point-based image stitching methods have a problem that stitching results are intensely affected by feature points. To solve this problem, deep learning-based image stitching technologies have recently been studied, but there are still many problems when there are few overlapping areas between images or large parallax. In addition, there is a limit to complete supervised learning because labeled ground-truth panorama images cannot be obtained in a real environment. Therefore, we produced three fisheye images with different camera centers and corresponding ground truth image through carla simulator that is widely used in the autonomous driving field. We propose image stitching model that creates a 360° panorama image with the produced fisheye image. The final experimental results are virtual datasets configured similar to the actual environment, verifying stitching results that are strong against various environments and large parallax.

Development of Artificial Intelligence Instructional Program using Python and Robots (파이썬과 로봇을 활용한 인공지능(AI) 교육 프로그램 개발)

  • Yoo, Inhwan;Jeon, Jaecheon
    • 한국정보교육학회:학술대회논문집
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    • 2021.08a
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    • pp.369-376
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    • 2021
  • With the development of artificial intelligence (AI) technology, discussions on the use of artificial intelligence are actively taking place in many fields, and various policies for nurturing artificial intelligence talents are being promoted in the field of education. In this study, we propose a robot programming framework using artificial intelligence technology, and based on this, we use Python, which is used frequently in the machine learning field, and an educational robot that is highly utilized in the field of education to provide artificial intelligence. (AI) education program was proposed. The level of autonomous driving (levels 0-5) suggested by the International Society of Automotive Engineers (SAE) is simplified to four levels, and based on this, the camera attached to the robot recognizes and detects lines (objects). The goal was to make a line detector that can move by itself. The developed program is not a standardized form of solving a given problem by simply using a specific programming language, but has the experience of defining complex and unstructured problems in life autonomously and solving them based on artificial intelligence (AI) technology. It is meaningful.

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Optimal Route Guidance Algorithm using Lidar Sensor (Lidar 센서를 활용한 최적 경로 안내 알고리즘)

  • Choi, Seungjin;Kim, Dohun;Lim, Jihu;Park, Sanghyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.400-403
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    • 2021
  • Algorithms for predicting the optimal route of vehicles are being actively sudied with the recent development of autonomous driving technology. Companies such as SK, Kakao, and Naver provide services that navigate the optimal route. They predicts the optimal path with information from the users in real time. However, they can predict the optimal route, but not optimal lane route. We proposes a system that navigates the optimal lane path with coordinates data from vehicles using Lidar sensor. The proposed method is a system that guides smooth lanes by acquiring time series coordinate data of a vehicle after performing the Lidar-based object detection method. we demonstrates the performance using actual acquired data from the experimental results.

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Design and Implementation of Dangerous of Image Recognition based Cup Contamination Measurement System (이미지 인식 기반의 컵 오염 여부 측정 시스템의 설계 및 구현)

  • Lee, Taejun;Chae, Heeseok;Lee, Sangwon;Kim, Jaemin;Jung, Hoekyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.213-215
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    • 2022
  • Recently, deep learning technology that processes images has been widely used in fire detection, autonomous driving, and defective product detection. In particular, in order to determine whether a product is contaminated or not, it can be identified through the contaminants passed from the existing sensor data, but technologies for recognizing cracks in products or contaminants themselves as images are being actively studied in various fields. In this paper, a system for classifying uncontaminated normal cups and contaminated cups through images was designed and implemented. The image was analyzed using an open image and a photographed image, and the image was analyzed by extracting the upper part of the cup image using Google Objectron for 3D object recognition. Through this study, it is thought that it will be used in various ways for research that can extract the contamination level of products required in the hygiene field based on images.

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A Study on the Understanding of Women by the Daesoon Thought and Its Contemporary Meanings (대순사상의 여성 이해와 그 현대적 의미)

  • Moon, Sun-young
    • Journal of the Daesoon Academy of Sciences
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    • v.21
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    • pp.255-284
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    • 2013
  • There are many discourses about 'religion and women,' but it is no exaggeration to say that there is none about 'religion and men.' This is because the existing religions have been male-centric and have produced legions of male-dominated cultures. In Catholic Church, even today, only men can become the Pope, and women are not allowed to enter priesthood. Meanwhile, in the Islamic cultural areas, the reality is that women are being victimized by men who do not recognize the bad habits such as honor killings, or honor crimes. It is certain that gender discrimination in religious and cultural areas cannot be overlooked. This study focuses on the understanding of women in the thought of Daesoonjinrihoe(大巡眞理會), that is, the Daesoon Thought, which claims to advocate world peace. Daesoonjinrihoe is understood as a thought which tries to overcome gender discrimination prevalent in the existing religions and presents the vision of a new religion which aims to realize a new world of peace by drawing a distinction between the Former Heaven and the Latter Heaven. This study examines the understanding of women by looking at the tenet of Daesoonjinrihoe that consists of 'YeumYangHapDeok(陰陽合德), SinInJoHwa(神人調化), HaeWon-SangSaeng(解冤相生), DoTongJinGyeong(道通眞境).' The tenet is thought of as the basis of creed on which the understanding of women by the Daesoon Thought can be grasped as it basically contains the essence of teaching of the order. In the Daesoon Thought, women have the same status as men; women can become holy and dignified beings by engaging in independent, active, and autonomous spiritual exercises, and serve as a driving force for the realization of the ideal world. This understanding of women by the Daesoon Thought contains the idea of peace which can turn 'the culture of discrimination' into 'the culture of equality,' and 'the culture of life destruction' into 'the culture of life care.'

Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation (강화학습 기반 3D 객체복원 데이터 획득 시뮬레이션 설계)

  • Young-Hoon Jin
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.11-16
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    • 2023
  • The technology of 3D reconstruction, primarily relying on point cloud data, is essential for digitizing objects or spaces. This paper aims to utilize reinforcement learning to achieve the acquisition of point clouds in a given environment. To accomplish this, a simulation environment is constructed using Unity, and reinforcement learning is implemented using the Unity package known as ML-Agents. The process of point cloud acquisition involves initially setting a goal and calculating a traversable path around the goal. The traversal path is segmented at regular intervals, with rewards assigned at each step. To prevent the agent from deviating from the path, rewards are increased. Additionally, rewards are granted each time the agent fixates on the goal during traversal, facilitating the learning of optimal points for point cloud acquisition at each traversal step. Experimental results demonstrate that despite the variability in traversal paths, the approach enables the acquisition of relatively accurate point clouds.

A Study on the Image/Video Data Processing Methods for Edge Computing-Based Object Detection Service (에지 컴퓨팅 기반 객체탐지 서비스를 위한 이미지/동영상 데이터 처리 기법에 관한 연구)

  • Jang Shin Won;Yong-Geun Hong
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.11
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    • pp.319-328
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    • 2023
  • Unlike cloud computing, edge computing technology analyzes and judges data close to devices and users, providing advantages such as real-time service, sensitive data protection, and reduced network traffic. EdgeX Foundry, a representative open source of edge computing platforms, is an open source-based edge middleware platform that provides services between various devices and IT systems in the real world. EdgeX Foundry provides a service for handling camera devices, along with a service for handling existing sensed data, which only supports simple streaming and camera device management and does not store or process image data obtained from the device inside EdgeX. This paper presents a technique that can store and process image data inside EdgeX by applying some of the services provided by EdgeX Foundry. Based on the proposed technique, a service pipeline for object detection services used core in the field of autonomous driving was created for experiments and performance evaluation, and then compared and analyzed with existing methods.

Shortwave Infrared Photodetector based on PbS Quantum Dots for Eye-Safety Lidar Sensors (Eye safety 라이다 센서용 황화납 양자점 기반 SWIR photodetector 개발)

  • Suji Choi;JinBeom Kwon;Yuntae Ha;Daewoong Jung
    • Journal of Sensor Science and Technology
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    • v.32 no.5
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    • pp.285-289
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    • 2023
  • Recently, the demand for lidar systems for autonomous driving is increasing, and research on Shortwave Infrared(SWIR) photodetectors for this purpose is being actively conducted. Most SWIR photodetectors currently being developed are based on InGaAs, and have the disadvantages of complex processes, high prices, and limitations in research due to monopoly. In addition, current SWIR photodetectors use lasers in the 905 nm wavelength band, which can pass through the pupil and cause damage to the retina. Therefore, it is required to develop a SWIR photodetector using a wavelength band of 1400 nm or more to be safe for human eyes, and to develop a material that can replace the proprietary InGaAs. PbS QDs are group 4-6 compound semiconductors whose absorption wavelength band can be adjusted from 1000 to 2700 nm, and have the advantage of being simple to process. Therefore, in this study, PbS QDs having an absorption wavelength peak of 1415 nm were synthesized, and a SWIR photodetector was fabricated using this. In addition, the photodetector's responsivity was improved by applying P3HT and ZnO NPs to improve electron hole mobility. As a result of the experiment, it was confirmed that the synthesized PbS QDs had excellent FWHM characteristics compared to commercial PbS QDs, and it was confirmed that the photodetector had a maximum current change of about 1.6 times.