• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.10-19
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• 2022

Recently, the Defense Advanced Research Projects Agency(DARPA) in the United States is studying a new concept of war called Mosaic Warfare, and MUM-T(Manned-Unmanned Teaming) through the division of missions between expensive manned and inexpensive unmanned aircraft is at the center. This study began with the aim of deriving the priority of autonomous functions according to the role of unmanned aerial vehicles in the present and present collaboration that is emerging along with the concept of mosaic warfare. The autonomous function of unmanned aerial vehicles between the presence and absence collaboration may vary in priority depending on the tactical operation of unmanned aerial vehicles, such as air-to-air, air-to-ground, and surveillance and reconnaissance. In this paper, ACE (Air Combat Evaluation), Skyborg, and Longshot, which are recently studied by DARPA, derive the priority of autonomous functions according to air-to-air collaboration, and use AHP analysis. The results of this study are meaningful in that it is possible to recognize the priorities of autonomous functions necessary for unmanned aircraft in order to develop unmanned aerial vehicles according to the priority of autonomous functions and to construct a roadmap for technology implementation. Furthermore, it is believed that the mass production and utilization of unmanned air vehicles will increase if one unmanned air vehicle platform with only essential functions necessary for air-to-air, air-to-air, and surveillance is developed and autonomous functions are expanded in the form of modules according to the tactical operation concept.

• ETRI Journal
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• v.45 no.5
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• pp.731-734
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• 2023

• Journal of Auto-vehicle Safety Association
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• v.15 no.1
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• pp.45-54
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• 2023

In the commercialization stage of level 4 or higher autonomous driving, the need for new legal system related to drive safely has increased in order to meet the improved level of technological development. Especially human drivers should not be legally accountable for road safety in the era of autonomous vehicles and thus safety standards for operation of autonomous vehicles are significant. To address this issue, the German Road Traffic Act was revised in 2021, adding provisions corresponding to the commercialization of self-driving vehicle of level 4 and in the similar context the Japanese Road Traffic Ac was amended in 2022. This Article draws implications for legislative discussions on driving-related responsibilities of driverless autonomous vehicle to ensure driving safety in Korea through recent amendments in Germany and Japan.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.7-12
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• 2022

Safety and security are the topmost priority in every environment. With the aid of Artificial Intelligence (AI), many objects are becoming more intelligent, conscious, and curious of their surroundings. The recent scientific breakthroughs in autonomous vehicular designs and development; powered by AI, network of sensors and the rapid increase of Internet of Things (IoTs) could be utilized in maintaining safety and security in our environments. AI based on deep learning architectures and models, such as Deep Neural Networks (DNNs), is being applied worldwide in the automotive design fields like computer vision, natural language processing, sensor fusion, object recognition and autonomous driving projects. These features are well known for their identification, detective and tracking abilities. With the embedment of sensors, cameras, GPS, RADAR, LIDAR, and on-board computers in many of these autonomous vehicles being developed, these vehicles can properly map their positions and proximity to everything around them. In this paper, we explored in detail several ways in which these enormous features embedded in these autonomous vehicles, such as the network of sensors fusion, computer vision and natural image processing, natural language processing, and activity aware capabilities of these automobiles, could be tapped and utilized in safeguarding our lives and environment.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.40-49
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• 2022

Remote-controlled and autonomous driving based on artificial intelligence are key elements required for unmanned combat vehicles. The required capability of such an unmanned combat vehicle should be expressed in reasonable required operational capability(ROC). To this end, in this paper, the requirements of an unmanned combat vehicle operated under a manned-unmanned teaming were analyzed. The functional requirements are remote operation and control, communication, sensor-based situational awareness, field environment recognition, autonomous return, vehicle tracking, collision prevention, fault diagnosis, and simultaneous localization and mapping. Remote-controlled and autonomous driving of unmanned combat vehicles could be achieved through the combination of these functional requirements. It is expected that the requirement analysis results presented in this study will be utilized to satisfy the military operational concept and provide reasonable technical indicators in the system development stage.

• 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.5
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• pp.117-132
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• 2022

The purpose of this study is to analyze factors that affect road users' acceptance of fully autonomous vehicles (level 4 or higher). A survey was done with drivers of general cars and pedestrians who share roads with fully autonomous vehicles. Five acceptability factors were selected: trust towards technology, compatibility, policy, perceived safety, and perceived usefulness. The effect on behavioral intention was analyzed using structural equation modeling (SEM). The perceived safety and trust towards technology were found to be very important in the acceptance of fully autonomous vehicles, regardless of the respondent, and policy was not influential. Compatibility and perceived usefulness were particularly influential factors for drivers. In order to improve the acceptance by road users, securing technical completeness of fully autonomous vehicles is important. Certification and evaluation of the safe driving ability of fully autonomous vehicles should be thoroughly performed, and based on the results, it is necessary to improve the perception by road users. It is necessary to positively recognize fully autonomous vehicles through education and publicity for road users and to support their smooth interaction.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.1-10
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• 2023

With the advent of the 4th industrial revolution era, interest in autonomous driving technology is increasing. Accordingly it is necessary to seek safe driving by recognizing surrounding situations using sensors attached to autonomous vehicles along with the applicability of existing traffic facilities to autonomous driving lanes and the utilization of HD maps. In this study, in order to deduce the role of sensor only physical facilities which recognized through a laser scanner on an autonomous vehicle developed to improve road and traffic infrastructure, through comparative analysis with existing road facilities such as road signs, safety signs, and gaze guidance facilities. Sign facilities can promote driving safety by allowing autonomous vehicles to perform specific actions directly. In order to promote safe driving by recognizing sign facilities by using sensors for autonomous vehicles, it is necessary to prepare standards for installation, management, and use, and it is considered that management and supervision should be carried out continuously according to the standards.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.31-39
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• 2021

This study collected 1,870 English news articles related to research and development of autonomous vehicles in order to identify various issues emerging in the research and development process of autonomous vehicles at home and abroad, and conducted topic modeling after data pre-processing. As a result of topic modeling, we extracted 20 topics, and we performed naming operations for topics and interpreted their meanings. A logical model for autonomous vehicle research and development projects was presented in response to the R&D process of input, activity, output, and outcome of derived topics. The analysis results of this study will be used as basic data to accurately determine the progress of domestic and foreign self-driving car research and development projects and prepare for the rapidly changing technology development.

• 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.