• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.5
• /
• pp.163-181
• /
• 2023

Improving the detection performance of facilities corresponding to the sensors of autonomous vehicles helps driving safety. In the road and transportation field, research is being conducted to improve the detection performance of sensors by road infrastructure or facilities. As part of this on the development of autonomous driving support infrastructure, the shape of traffic cones and drums to ensure sufficient LiDAR detection performance even rainy conditions and maintain the line-of-sight guidance function in construction zones improvement effect. The principle was to increase reflection performance and ensure no significant difference in shape from existing facilities. Traffic cones were manufactured in square pyramid shapes instead of cones, and drums were manufactured in hexagonal and octagonal pillar shapes instead of cylinders. LiDAR detection data for the facility was confirmed on a clear day and with 20 mm/h and 40 mm/h rainfall. The detection performance of the square pyramid-shaped traffic cone and octagonal column-shaped drum was to the existing facility. On the other hand, deviations occurred due to repeated measurements, and significance could not be confirmed through statistical analysis. By reflecting these results, future studies will seek a form in which data can be obtained uniformly despite the diversity of measurement environments.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.21-30
• /
• 2024

In this paper, we propose a method to build a sample dataset of the features of eight sensor-only facilities built as infrastructure for autonomous cooperative driving. The feature extracted from point cloud data acquired by LiDAR and build them into the sample dataset for recognizing the facilities. In order to build the dataset, eight sensor-only facilities with high-brightness reflector sheets and a sensor acquisition system were developed. To extract the features of facilities located within a certain measurement distance from the acquired point cloud data, a cylindrical projection method was applied to the extracted points after applying DBSCAN method for points and then a modified OTSU method for reflected intensity. Coordinates of 3D points, projected coordinates of 2D, and reflection intensity were set as the features of the facility, and the dataset was built along with labels. In order to check the effectiveness of the facility dataset built based on LiDAR data, a common CNN model was selected and tested after training, showing an accuracy of about 90% or more, confirming the possibility of facility recognition. Through continuous experiments, we will improve the feature extraction algorithm for building the proposed dataset and improve its performance, and develop a dedicated model for recognizing sensor-only facilities for autonomous cooperative driving.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.172-191
• /
• 2023

This study was undertaken to strategize the mixed traffic operation of autonomous vehicles in the pilot zone. This was achieved by analyzing the changes expected when autonomous vehicles are mixed in the autonomous vehicle pilot zone. Although finding a safe and efficient traffic operation strategy is required for the pilot zone to serve as a test bed for autonomous vehicles, there is no available operation strategy based on the mixture of autonomous vehicles. In order to presents a traffic operation strategies for each period of autonomous vehicle introduction, traffic efficiency and safety analysis was performed according to the autonomous vehicle market percentage rate. Based on the analysis results, the introduction stage was divided into introductory stage, transition period, and stable period based on the autonomous vehicle market share of 30% and 70%. This study presents the following traffic operation strategies. Considering the traffic flow operation strategy, we suggest the advancement of the existing road infrastructure at the introductory stage, and operating an autonomous driving lane and the mileage system during the transition period. We also propose expanding the operation of autonomous driving lanes and easing the speed limit during the stable period. In the traffic safety strategy, we present a manual and legal system for responding to autonomous vehicle accidents in the introductory stage, an analysis of the causes of autonomous vehicle accidents and the implementation of preventive policies in the transition period, and the advancement of the autonomous system and the reinforcement of the security system during the stable period. Through the traffic operation strategy presented in this study, we foresee the possibility of preemptively responding to the changes of traffic flow and traffic safety expected due to the mixture of autonomous vehicles in the autonomous vehicle pilot zone in the future.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.2
• /
• pp.45-50
• /
• 2022

The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.

• The Journal of Society for e-Business Studies
• /
• v.21 no.1
• /
• pp.79-90
• /
• 2016

Autonomous knowledge service, a fully-automated and pervasive service for knowledge acquisition and support based on the power of recent ITs is gaining tremendous interest more and more, as not only the level of users' intelligence increases but also the maturity of IT infrastructure improves. Conventional approaches of knowledge service, however, could not satisfy users because they usually provided undesired knowledge which had been acquired without considering users' want. In other words, knowledge acquisition and distribution were separately performed. This research, therefore, suggests an amended autonomous knowledge service framework by fully-automating the whole phases of knowledge life cycle, from knowledge acquisition to distribution. ASKs, the prototype system of this research, is also implemented by defining and specifying component technologies which constituently compose suggested framework. More user-friendly and applicable way of knowledge service will be derived and facilitated through this research.

• Journal of the Korean Institute of Gas
• /
• v.24 no.3
• /
• pp.1-10
• /
• 2020

This paper describes the development of a smart advanced metering infrastructure(AMI) architecture and services for using smart metering in gas industry. A general gas AMI system is composed of a smart gas meter, IoT network, the AMI platform, and an operation management system with security functions. The proposed gas AMI platform supports two-way communication between smart metering devices and AMI services and is applied by oneM2M standard to support interoperability between various types of metering devices and heterogeneous IoT networks. To demonstrating AMI system with the proposed platform, we installed about 2,900 smart gas meters in real environments and operated AMI systems for one year. We verified that about 94% of gas meters are normally worked and AMI services are stably operated without error or malfunction.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.5
• /
• pp.566-573
• /
• 2021

In this study, safety management procedures were developed based on domestic and foreign guidelines and related maritime law to ensure the safe development and implementation of smart autonomous ship technology and Samsung Heavy Industry. The safety management procedure was developed according to the guidelines for (MASS) sea trials (MSC.1/Circ.1604, Annex: Interim guidelines for MASS trials), proposed by International Maritime Organization (IMO) for the relevant authorities and stakeholders of MASS to properly conduct tests of systems and infrastructure related to safety and environmental protection. The developed safety management procedure applies to the maritime demonstration test of a system applying autonomous navigation element technology mounted as a navigation aid on a ship operating under a watch system, while complying with the environmental protection and navigation safety of the coast of Korea.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.12
• /
• pp.1500-1505
• /
• 2019

Currently, as part of the ICT Smart City, the company is building C-ITS(Cooperative-Intelligent Transport Systems) for solving urban traffic problems. In order to realize autonomous driving service with C-ITS, the role of advanced road infrastructure is important. In addition to the study of mid- to long-term C-ITS and autonomous driving services, it is necessary to present more realistic solutions for road traffic safety in the short term. Therefore, in this paper, we propose a highway accident detection alarm system that can detect and analyze traffic flow and risk information, which are essential information of C-ITS, based on IoT guard rail and provide immediate alarm and remote control. Intelligent IoT guard rail is expected to be used as an intelligent advanced road infrastructure that provides data at actual road sites that are required by C-ITS and self-driving services in the long term.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.3
• /
• pp.132-145
• /
• 2020

By coming of the 4th industrial revolution era, HD map have became a key infrastructure for determining precise location of autonomous driving in areas of futuristic cars, logistics and robots. Autonomous vehicles have became more dependent on HD map to determine the exact location of objects detected by various sensors such as LiDAR, GNSS, Radar, and stereo cameras as well as self-location decisions. By actualizing autonomous driving and C-ITS technologies, the demand for precise information on HD map have increased. And also the demand for the creation of new information based on the convergence of various changes and real-time information have increased. In this study, domestic and international HD map standards and related environments have analyzed. Based on this, usability has researched which comparison with standard HD map established by various institutions. Additionally, usability of standard HD map have studied for applying actual autonomous vehicles by reworking HD map. By the result of study, standard HD map have well established to use by various institutions. If further research about layer classification and definition by institutions will carried out based on this study, it has expected that and efficient establishment and renewal of HD map will take place.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.4
• /
• pp.611-616
• /
• 2018

With the recent increase in awareness of the diversification of patterns of warfare and security, technological evolution is occurring in the field of autonomous defense robots. As defense science and technology develops with the development of the concept of military utilization focusing on human lives and economic operation, the importance of autonomous robots in the effect-oriented future battlefield is increasing. The major developed countries have developed core technologies, investment strategies, priorities, data securing strategies and infrastructure development related to the field of autonomous defense robots, and research activities such as technology planning and policy strategy for autonomous defense robots in Korea have already begun. In addition, the field of autonomous defense robots encompasses technologies that represent the fourth industrial revolution, such as artificial intelligence, big data, and virtual reality, and so the expectations for this future area of technology are very high. It is difficult to predict the path of technological development due to the increase in the demand for new rather than existing technology. Moreover, the selection and concentration of strategic R&D is required due to resource constraints. It is thought that a preemptive response is needed. This study attempts to derive 6 new technologies that will shape the future of autonomous defense robots and to obtain meaningful results through an empirical study.