• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.258-272
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• 2022

The technology implementation method was diversified into an 'autonomous cooperative driving' method to overcome the limitations of a stand-alone autonomous vehicle with vehicle sensor-based autonomous driving. The autonomous cooperative driving method involves exchanging information between roadside infrastructure and autonomous vehicles. In this process, the concept of dynamic information (LDM), a target of cooperation, was established. But, evaluation methods and standards for dynamic information have not been established. Therefore, this study, a dynamic information evaluation method based on information on pedestrians within the moving objects. In addition, autonomous cooperative driving was demonstrated, and dynamic information was also verified through the evaluation method. The significance of this study is that it established the dynamic information evaluation methodology for autonomous cooperative driving for the first time. Based on this, this study is expected to contribute to the application of safe autonomous cooperative driving technology to the field.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.91-104
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• 2022

The operational design domain (ODD) of autonomous vehicles needs to be expanded on highways and urban roads in light of the substantial commercialization of Level 3 autonomous vehicles. Therefore, this study developed a specific infrastructure autonomous vehicle-based cooperative driving service to ensure the driving safety of autonomous vehicles on city roads. The traffic operation efficiency, safety evaluation, and core evaluation indices for each service were selected and analyzed to study the effect of each service. The result of the analysis confirmed that the traffic operation efficiency and safety of autonomous vehicles were improved through the V2X communication-based autonomous cooperative driving service. On the whole, the significance of this study is in deriving the effect of the autonomous cooperative driving service based on V2X communication on urban roads with interrupting traffic flow.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.34-42
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• 2023

Simulation-based virtual testing is known to be a major requirement for verifying the safety of autonomous driving functions. However, in the simulation environment, there is a difficulty in that all driving environments related to the autonomous driving system must be realistically modeled. In particular, C-ITS (Cooperative-Intelligent Transport Systems) is essential for urban autonomous driving of Lv.4, but the approach to modeling for C-ITS service in the MILS (Model in the Loop Simulation) environment is not yet clear. Therefore, this paper aims to deal with V2X (Vehicle to Everything) modeling methods to effectively apply C-ITS-based autonomous cooperative driving services in the MILS environment. First, major C-ITS services and use cases for autonomous cooperative driving are analyzed, and a modeling method of V2X signals for C-ITS service simulation is proposed. Based on the modeled V2X messages, the validity of the proposed approach is reviewed through simulations on the C-ITS service use case.

• 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.

• 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.

• 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 Advanced Navigation Technology
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• v.22 no.5
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• pp.391-399
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• 2018

V2X communication is a technology in which a vehicle exchanges information with various entities such as other vehicles, infrastructure, networks, pedestrians, etc. through a wired or wireless network. Recently, V2X communication technology has been steadily developed and recently it has played an important role in autonomous cooperation driving technology combined with autonomous vehicle technology. Autonomous vehicles can utilize the external information received via V2X communication to extend the recognition range of existing sensors and to support more safe and natural autonomous driving. In order to operate these autonomous cooperative vehicles on public roads, the security and reliability of autonomous V2X communication should be verified in advance. In this paper, we present test scenarios and test procedures of secure V2X communication for cooperative automated driving and present verification results.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.81-91
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• 2021

Last year, the Autonomous Vehicle Act was enacted to respond to deployment of autonomous vehicles. But the Act stipulates the operation of autonomous vehicle pilot zones, In addition, in order to analyze autonomous vehicle accidents and establish a reasonable damage compensation system, the Automobile Damage Compensation Guarantee Act was revised. But, It is necessary to seek plans for institutional development such as detailed concepts of self-driving cars and driving, a security certification system for securing safety of autonomous cooperative driving, and enhancement of the effectiveness of special cases related to personal information processing. I would like to seek ways to improve the legal system to respond reasonably to the deployment of autonomous vehicles.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.617-627
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• 2021

In the field of on-road motor vehicles, the level for autonomous driving technology is defined according to J3016, proposed by Society of Automotive Engineers (SAE) International. However, in the field of agricultural machinery, different standards are applied by country and manufacturer, without a standardized classification for autonomous driving technology which makes it difficult to clearly define and accurately evaluate the autonomous driving technology, for agricultural machinery. In this study, a method to classify the autonomy levels for autonomous agricultural machinery (ALAAM) is proposed by modifying the SAE International J3016 to better characterize various agricultural operations such as tillage, spraying and harvesting. The ALAAM was classified into 6 levels from 0 (manual) to 5 (full automation) depending on the status of operator and autonomous system interventions for each item related to the automation of agricultural tasks such as straight-curve path driving, path-implement operation, operation-environmental awareness, error response, and task area planning. The core of the ALAAM classification is based on the relative roles between the operator and autonomous system for the automation of agricultural machines. The proposed ALAAM is expected to promote the establishment of a standard to classify the autonomous driving levels of self-propelled agricultural machinery.