• 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.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.1-15
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• 2022

In order to trust and use autonomous vehicles, safe driving on the road must be guaranteed. For this, the first infrastructure to be equipped with autonomous driving is traffic safety facility. On the other hand, autonomous vehicles(Level 3) and general vehicles are driving on the road, it is necessary to additionally manage existing general traffic safety facilities. In this study, a field management system for traffic safety facilities based on autonomous driving infrastructure was studied, and a pilot field management system was implemented in the demonstration area(Pangyo). The pilot system consists of a GNSS(Global Navigation Satellite System) receiver, a field management equipment, and a field management app. As a result of field demonstration,, it was confirmed that traffic safety facility information was easily transmitted and received even in downtown areas and that could be efficiently operated and managed. It is expected that the results of this study will be used as reference materials for the spread of autonomous driving infrastructure to local governments and infrastructure construction in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.123-133
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• 2024

Existing autonomous driving technology has been developed based on sensors attached to the vehicles to detect the environment and formulate driving plans. On the other hand, it has limitations, such as performance degradation in specific situations like adverse weather conditions, backlighting, and obstruction-induced occlusion. To address these issues, cooperative autonomous driving technology, which extends the perception range of autonomous vehicles through the support of road infrastructure, has attracted attention. Nevertheless, the real-time analysis of the 3D centroids of objects, as required by international standards, is challenging using single-lens cameras. This paper proposes an approach to detect objects and estimate the centroid of vehicles using the fixed field of view of road infrastructure and pre-measured geometric information in real-time. The proposed method has been confirmed to effectively estimate the center point of objects using GPS positioning equipment, and it is expected to contribute to the proliferation and adoption of cooperative autonomous driving infrastructure technology, applicable to both vehicles and road infrastructure.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.73-81
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• 2023

Globalized cities are currently showing changes due to autonomous driving (AD). It is also maximizing globalization connections in cities where autonomous mobility is as complex as AD. The purpose of this study is to reveal that cities that realize AD and mobility will grow into globalized cities. Several cities, including New York and Shanghai, have attempted and are in progress, but failed cities are increasing. Although the technology of AD and the trust of citizens are prioritized, the city that has built the city's infrastructure is expected to be a city that has succeeded in AD. This is because commercialized cities or AVs will become hubs for mobility globalization, excluding rapid climate change or AV companies, and empirical analysis has been conducted that if AVs fail in metropolitan New York due to urban complexity (population density), urban economy size (GRDP), patents, number of consumers, infrastructure public EV chargers, and road quality. It examines whether the realization of AD by region and country affects overall national innovation. As a result, even if AV succeeds in large cities such as New York, Seoul, which has a higher population density (complexity), has a negative meaning, and a more similar Tokyo has a positive meaning. It can be seen that regional research on AV should also be prioritized in large cities such as Shanghai. This means that in order for AV to be realized in each city, the construction of AI infrastructure data must be actively changed to establish globalization of cities for economic growth as autonomous mobility.

• Journal of Communications and Networks
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• v.8 no.4
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• pp.378-390
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• 2006

Many distributed applications build overlays on top of the Internet. Several unsolved issues at the network layer can explain this trend to implement network services such as multicast, mobility, and security at the application layer. On one hand, overlays creating basic topologies are usually limited in flexibility and scalability. On the other hand, overlays creating complex topologies require some form of application level addressing, routing, and naming mechanisms. Our aim is to design an efficient and robust addressing, routing, and naming infrastructure for these complex overlays. Our only assumption is that they are deployed over the Internet topology. Applications that use our middleware will be relieved from managing their own overlay topologies. Our infrastructure is based on the separation of the naming and the addressing planes and provides a convergence plane for the current heterogeneous Internet environment. To implement this property, we have designed a scalable distributed k-resilient name to address binding system. This paper describes the design of our overlay infrastructure and presents performance results concerning its routing scalability, its path inflation efficiency and its resilience to network dynamics.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.139-146
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• 2021

Ahead of the commercialization of autonomous vehicles, it's application should be considered into the current transportation infrastructure. Under limited traffic circumstances, effective set of lane change rules alone could bring benefits to the autonomous driving system. In this study, a cooperative movement (local platooning) plan with limited vehicles associated as pocket driving, aiming at effective movement between vehicles in urban environment was proposed. Under congested roadway condition, the gaussian gap between vehicles was introduced to secure gap acceptance for safe lane change maneuver. Proposed lane change method showed 86.6% delay reduction along with traffic volume improvement. This result could be considered as a crucial factor in designing a next-generation roadway infrastructure with autonomous driving.

• Journal of Auto-vehicle Safety Association
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• v.11 no.3
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• pp.19-29
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• 2019

Recently, autonomous vehicles have been studied actively. Autonomous vehicles can detect objects around them using their on board sensors, estimate collision probability and maneuver to avoid colliding with objects. Many algorithms are suggested to prevent collision avoidance. However there are limitations of complex and diverse environments because algorithm uses only the information of attached environmental sensors and mainly depends on TTC (time-to-Collision) parameter. In this paper, autonomous driving algorithm using I2V communication-based cooperative sensing information is developed to cope with complex and diverse environments through sensor fusion of objects information from infrastructure camera and object information from equipped sensors. The cooperative sensing based autonomous driving algorithm is implemented in autonomous shuttle bus and the proposed algorithm proved to be able to improve the autonomous navigation technology effectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.595-601
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• 2018

The era of autonomous vehicles, which drive themselves and in whose operation the driver does not intervene, is fast approaching. The safety of autonomous vehicles can be guaranteed only if they recognize the road infrastructure. However, the road infrastructure consists of road safety facilities, traffic operation systems, and cross-sectional concerns, which include a variety of components, such as types, shapes, and sizes. Therefore, it is necessary to prioritize the road information. This study was conducted to select the priority with which the road infrastructure attributes should be acquired using the AHP (Analytical Hierarchy Process) method. The road infrastructure attributes were categorized into 2 levels, levels 1 and 2, which consisted of 3 and 26 types of attributes, respectively. As a result of the AHP analysis, it was found that the highest priorities of the road infrastructure are the road safety facilities, traffic operation systems and cross sectional concerns. Also, in level-2, the priorities of the safety barriers (road safety facilities), traffic signals (traffic operation systems), and the median (cross sectional) are the highest. Also, this study provides application examples of road infrastructure extraction with the Point Cloud. The results are expected to support the recognition of technology for autonomous vehicles.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.450-455
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• 2021

In this paper, we introduce the contents of research on the establishment of an evaluation environment for autonomous cooperative driving platform for commercial vehicles based on V2X communication. For the evaluation of the autonomous cooperative driving platform based on V2X communication, various standards, standards, and guidelines for test evaluation should be developed and provided to the test subject, along with the establishment of test beds such as roads and V2X infrastructure that can apply various driving scenarios. do. In addition, based on this, various reference equipment and test equipment for actual test and evaluation should be developed. In this paper, various technologies, standards, equipment, and construction infrastructure developed to construct the evaluation environment for autonomous cooperative driving platform for commercial vehicles based on V2X communication are introduced.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.190-201
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• 2023

Securing transportation safety infrastructure technology for Lv.4 connected autonomous driving is very important for the spread of autonomous vehicles, and the safe operation of level 4 autonomous vehicles in adverse weather has limitations due to the development of vehicle-only technology. We developed the radar-enabled AI convergence transportation entities detection system. This system is mounted on fixed and mobile supports on the road, and provides excellent autonomous driving situation recognition/determination results by converging transportation entities information collected from various monitoring sensors such as 60GHz radar and EO/IR based on artificial intelligence. By installing such a radar-enabled AI convergence transportation entities detection system on an autonomous road, it is possible to increase driving efficiency and ensure safety in adverse weather. To secure competitive technologies in the global market, the development of four key technologies such as ① AI-enabled transportation situation recognition/determination algorithm, ② 60GHz radar development technology, ③ multi-sensor data convergence technology, and ④ AI data framework technology is required.