• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.2
• /
• pp.145-150
• /
• 2016

The capability of accurate positioning and tracking is necessary to implement an unmanned autonomous driving system. The moving-baseline GPS Technique is a promising candidate to mitigate positioning errors of conventional GPS system. It provides accurate positioning data based on the phase difference between received signals from multiple GPS antennas mounted on the same platform. In this paper, we propose a dual-band dual-circularly-polarized antenna suitable for the moving-baseline GPS. The proposed antenna operates at GPS L1 and L2 bands, and fed by the side of the antenna instead of the bottom. The antenna is firstly designed by calculating theoretical values of key parameters, and then optimized by means of 3D full-wave simulation software. Simulation and measurement results show that the optimized antenna offers 6.1% and 3.7% bandwidth at L1 and L2, respectively, with axial ratio bandwidth of more than 1%. The size of the antenna is $73mm{\times}73mm{\times}6.4mm$, which is small and low-profile.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.12
• /
• pp.1950-1958
• /
• 2016

Today, technique for precisely positioning vehicles is very important in C-ITS(Cooperative Intelligent Transport System), Self-Driving Car and other information technology relating to transportation. Though the most popular technology for vehicle positioning is the GPS, its accuracy is not reliable because of large delay caused by multipath effect, which is very bad for realtime traffic application. Therefore, in this paper, we proposed the Vision-Based High Accuracy Vehicle Positioning Technology. At the first step of proposed algorithm, the ROI is set up for road area and the vehicles detection. Then, center and four corners points of found vehicles on the road are determined. Lastly, these points are converted into aerial view map using homography matrix. By analyzing performance of algorithm, we find out that this technique has high accuracy with average error of result is less than about 20cm and the maximum value is not exceed 44.72cm. In addition, it is confirmed that the process of this algorithm is fast enough for real-time positioning at the $22-25_{FPS}$.

• Journal of the Institute of Convergence Signal Processing
• /
• v.22 no.3
• /
• pp.110-115
• /
• 2021

With the era of the 4th Industrial Revolution, education on artificial intelligence is one of the important topics. However, since existing education is aimed at knowledge, it is not suitable for developing the active problem-solving ability and AI utilization ability required by artificial intelligence education. To solve this problem, we proposes PBL-based education method in which learners learn in the process of solving the presented problem. The problem presented to the learner is a completed project. This project consists of three types: a classification model, the training data of the classification model, and the block code to be executed according to the classified result. The project works, but each component is designed to perform a low level of operation. In order to solve this problem, the learners can expect to improve their computational thinking skills by finding problems in the project through testing, finding solutions through discussion, and improving to a higher level of operation.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.5
• /
• pp.139-146
• /
• 2022

With the recent development of the Internet of Things (IoT) and the convergence of vehicles and IT technologies, high-performance applications such as autonomous driving are emerging, and multi-access edge computing (MEC) has attracted lots of attentions as next-generation technologies. In order to provide service to these computation-intensive tasks in low latency, many methods have been proposed to partition tasks so that they can be performed through cooperation of multiple MEC servers(MECSs). Conventional methods related to task partitioning have proposed methods for partitioning tasks on vehicles as mobile devices and offloading them to multiple MECSs, and methods for offloading them from vehicles to MECSs and then partitioning and migrating them to other MECSs. In this paper, the performance of task partitioning methods using offloading and migration is compared and analyzed in terms of service delay, blocking rate and energy consumption according to the method of selecting partitioning targets and the number of partitioning. As the number of partitioning increases, the performance of the service delay improves, but the performance of the blocking rate and energy consumption decreases.

• The Journal of the Korea Contents Association
• /
• v.21 no.12
• /
• pp.375-383
• /
• 2021

Due to COVID-19, people are building new lifestyles such as online shopping, online travel, and video conferencing by limiting going out and gatherings. Such rapid social change is causing new problems and deepening existing problems at the same time. In particular, as online consumption increases significantly, traffic congestion, air pollution, and the heavy workload of delivery drivers are deepening in the daily logistics industry, and face-to-face delivery is emerging as a new problem. With the advent of the 4th industrial revolution, unmanned delivery using drones, artificial intelligence, and autonomous driving is emerging as an alternative to the existing logistics industry. However, space for logistics facilities and securing additional logistics sites due to drone flight are emerging as new problems to be solved. Therefore, it is intended to link additional services such as logistics movement, storage, and delivery by utilizing the existing transportation business, the subway, as a space for a logistics facility for drones that can solve existing problems and new problems.

• Electronics and Telecommunications Trends
• /
• v.32 no.4
• /
• pp.67-77
• /
• 2017

최근 이슈가 되고 있는 자율주행차(Autonomous vehicle 또는 Self-driving car)를 실현하기 위해서는, 다양한 환경에서도 차량에 대한 끊김 없는 연결을 제공하는 커넥티드카(Connected car) 기술이 필수적이다. 현재 커넥티드카를 구현하기 위한 차량 네트워크(Vehicular network) 기술은 교통시스템 인프라 기반의 단일홉(Single-hop) 무선통신 기술이 주를 이루고 있다. 이러한 단일홉 통신은 커버리지가 교통시스템 인프라가 구축된 지역으로 제한된다. 따라서 차량 네트워크가 현재보다 더욱 넓은 지역을 커버하기 위해서는 차량 자체가 이동형 라우터 역할을 수행하여 차량 간의 전달을 통해 정보를 원거리로 전달할 수 있는 다중홉(Multi-hop) 통신 도입이 필요하다. 다중홉 차량 네트워크는 차량의 높은 동적 특성으로 인해 다수의 도전적인 기술적 이슈들을 가진다. 본고에서는 이러한 기술 이슈 중 차량 네트워크의 높은 이동성으로 발생할 수 있는 종단 노드 간 비연결성을 해결할 수 있는 기술인 지연감내형 차량 네트워킹(Delay-tolerant vehicular networking) 기술에 대한 주요 연구 동향을 살펴보고자 한다. 이를 위해 먼저 지연감내형 차량 네트워킹의 기술적 배경 및 주요 관련 기술들을 분석하고 이를 기반으로 향후 연구개발이 필요한 기술 이슈들을 정리한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.3
• /
• pp.83-88
• /
• 2020

With developing vehicle and communication technologies, cars can communicate with road-side infrastructures and among other cars. As autonomous driving cars have been developed, the cars are equipped with many sensors and powerful processing units. There are many studies related to provide cloud services to users by using available resources of connected cars. In this paper, we proposed a dynamic task size decision scheme that considers communication environment between a vehicle and a base station as well as available resources while allocating a proper task to each vehicle. Simulation results based on the proposed model show that a vehicle can complete its allocated task when we considers available resources and communication environments.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.1
• /
• pp.123-128
• /
• 2017

This paper deals with performing missions through autonomous navigation using camera and other sensors. Extracting pose of the car is necessary to navigate safely within the given road. Homography is used to find it. Color image is converted into grey image and thresholding and edge is used to find control points. Two control ponits are converted into world coordinates using homography to find the angle and position of the car. Color is used to find traffic signal. It was confirmed that the given tasks performed well through experiments.

• The Journal of Korea Robotics Society
• /
• v.14 no.2
• /
• pp.122-130
• /
• 2019

Collecting a rich but meaningful training data plays a key role in machine learning and deep learning researches for a self-driving vehicle. This paper introduces a detailed overview of existing open-source simulators which could be used for training self-driving vehicles. After reviewing the simulators, we propose a new effective approach to make a synthetic autonomous vehicle simulation platform suitable for learning and training artificial intelligence algorithms. Specially, we develop a synthetic simulator with various realistic situations and weather conditions which make the autonomous shuttle to learn more realistic situations and handle some unexpected events. The virtual environment is the mimics of the activity of a genuine shuttle vehicle on a physical world. Instead of doing the whole experiment of training in the real physical world, scenarios in 3D virtual worlds are made to calculate the parameters and training the model. From the simulator, the user can obtain data for the various situation and utilize it for the training purpose. Flexible options are available to choose sensors, monitor the output and implement any autonomous driving algorithm. Finally, we verify the effectiveness of the developed simulator by implementing an end-to-end CNN algorithm for training a self-driving shuttle.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.73-75
• /
• 2022

Scene Text Recognition is a technology used in the field of artificial intelligence that requires manless robot, automatic vehicles and human-computer interaction. Though scene text images are distorted by noise interference, such as illumination, low resolution and blurring. Unlike previous studies that recognized only English, this paper shows a strong recognition accuracy including various characters, English, Korean, special character and numbers. Instead of selecting only one class having the highest probability value, a candidate word can be generated by considering the probability value of the second rank as well, thus a method can be corrected an existing language misrecognition problem.