• Journal of Information Technology Applications and Management
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• v.29 no.6
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• pp.1-12
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• 2022

In recent years, technological competition in the automobile sector is accelerating. This study analyzes the status of patents from a global perspective of three promising future items that Korea has selected as core technologies in the field of autonomous driving,. And the technological cooperation ecosystem was identified through network analysis centered on scientific metrology. As a result of the analysis, it was confirmed that the growth of individual technologies has been strengthened in recent years, and although key source technologies have been largely preempted in major global countries, a close cooperative ecosystem between institutions, companies, and universities in major countries has not yet been formed. Specifically, the US and Japan have the technological leadership, while China is rapidly rising, and Korea is chasing after it as a latecomer. Therefore, it is necessary to continuously strengthen technological cooperation such as R&D of core technology to overcome technological limitations and strengthening of infrastructure construction, attracting excellent foreign talents and international exchanges. This analysis is meaningful in that it explores the global status of Korea's technology and the possibility of technological cooperation from various perspectives in the future from the viewpoint of preoccupation of future technology, rather than grasping the trend of a specific technology.

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

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.3
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• pp.180-187
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• 2014

This paper introduces reliable multicast MAC protocol for cooperative unmanned vehicles. cooperative unmanned vehicles communicate with infrastructure and other unmanned vehicles in order to increase driving safety. They exchange information related to driving and thus it requires real-time and reliable multicast. However, the international vehicular communication standard, IEEE 802.11p WAVE, does not provide a reliable multicast scheme on the MAC layer. To address the problems of reliability, we propose a reliable multicast protocol called WiVCL, which avoids contention and collision. Our evaluation shows that the WiVCL achieves a high degree of reliability and real-time features.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.453-464
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• 2012

This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.208-218
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• 2023

Research on autonomous vehicles is being actively conducted, and the effort to commercialize them is underway in several countries. In Korea, platform construction projects are being carried out under the supervision of the Ministry of Land, Infrastructure, and Transport to achieve autonomous cooperative driving. To enable a flawless infrastructure, there is a requirement to build a safe security agency responsible for the secure operations of the entire process. However, there is no traffic ISAC in Korea that performs these roles. This paper analyzes related bills and acts of the other domestic security institutions currently in operation. Based on these results, we suggest appropriate directions to modify the current laws related to the C-ITS system. Finally, we propose a suitable plan to establish and operate a C-ITS ISAC.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.224-239
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• 2023

C-ITS (Cooperative-Intelligent Transportation System) refers to user safety-oriented technology and systems that provide forward traffic situation information based on a two-way wireless communication technology between vehicles or between vehicles and infrastructure. Since the Daejeon-Sejong pilot project in 2016, the C-ITS infrastructure has been installed at various locations to provide C-ITS safety services through highway and local government demonstration projects. In this study, a methodology was developed to verify the effectiveness of the warning information using individual vehicle data collected through the Gwangju Metropolitan City C-ITS demonstration project. The analysis of the effectiveness was largely divided into driving behavior impact analysis and environmental analysis. Compliance analysis and driving safety evaluation were performed for the driving impact analysis. In addition, to supplement the inadequate collection of Probe Vehicle Data (PVD) collected during the C-ITS demonstration project, Digital Tacho Graph ( DTG ) data was additionally collected and used for effect analysis. The results of the compliance analysis showed that drivers displayed reduced driving behavior in response to warning information based on a sufficient number of valid samples. Also, the results of calculating and analyzing driving safety indicators, such as jerk and acceleration noise, revealed that driving safety was improved due to the provision of warning information.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.161-172
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• 2023

Autonomous driving vehicles recognize the surroundings through various sensors mounted on the vehicle and control the vehicle based on the collected information. The level of autonomous driving technology is improving due to the development of sensor technology and algorithms that process collected data, but the implementation of perfect autonomous driving technology has not been achieved. To overcome these limitations, through autonomous cooperative driving centered on infrastructure. In this study, developed a position correction sign that provides a reference for positioning of autonomous vehicles. First of all, an analysis was performed on the current status of positioning technology for autonomous driving. And measure the number of point clouds for the 1st sample consisting of two square reflective surfaces and 2nd sample that increased the vertical length of each reflective surface. Experimental results show that both primary and secondary products are installed at least 15 m apart It could be recognized as a sensor, and it was confirmed that the secondary production that increased the length of the top and bottom had a higher number of point clouds than the primary production and better expressed the shape of the facility.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.6
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• pp.251-261
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• 2019

The importance of autonomous driving systems that utilize V2X services such as V2V(Vehicle to Vehicle) and V2I(Vehicle to Infrastructure) for safer and more comfortable driving is increasing with the recent development of autonomous vehicles. Partly autonomous vehicles based on environmental sensors have limitations for predicting and determining areas beyond the recognition distance of the mounted sensors and in response to atypical objects that are difficult to detect. Therefore, it is important to utilize the V2X service to improve the limit of sensor detection performance and to make driving safer and more comfortable. However, there may be an accident risk of autonomous vehicles due to incorrect information provided by V2X. Thus, the application of technology to prevent this needs to be considered. In this pater, we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to derive the risk sources of autonomous vehicles due to V2I malfunctions by using the communication between vehicles and infrastructure among V2X. We also developed ASIL ratings based on the simulations and real vehicle tests of the malfunctions of major cases of usnig V2I.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.21-30
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• 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
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.