• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.209-214
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• 2023

In the future, as autonomous vehicles become popular at home and abroad, the frequency of accidents involving autonomous vehicles is also expected to increase. In particular, when a fully autonomous vehicle is operated, various criminal/civil problems such as sexual violence, assault, and fraud between passengers may occur as well as the vehicle accident itself. In this case, forensics for accidents involving autonomous vehicles and accidents involving passengers in the vehicles are also about to change. This paper reviewed the types of security threats of autonomous vehicles, methods for maintaining the integrity of evidence data using blockchain technology, and research on digital forensics. Through this, it was possible to describe threats that would occur in autonomous vehicles using blockchain technology and forensic techniques for each type of accident in a scenario-type manner. Through this study, a block that helps forensics of self-driving vehicles before and after accidents by investigating forensic security technology of domestic and foreign websites to respond to vulnerabilities and attacks of autonomous vehicles, and research on block chain security of research institutes and information security companies. A chain method was proposed.

• Electrical & Electronic Materials
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• v.19 no.11
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• pp.19-28
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• 2006

• Korea Multimedia Society
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• v.14 no.1
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• pp.31-41
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• 2010

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.369-374
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• 2014

Path generation methods are required for safe and efficient driving in unmanned autonomous vehicles. There are two kinds of paths: global and local. A global path consists of all the way points including the source and the destination. A local path is the trajectory that a vehicle needs to follow from a way point to the next in the global path. In this paper, we propose a novel method for local path generation through machine learning, with an effective curve function used for initializing the trajectory. First, reinforcement learning is applied to a set of candidate paths to produce the best trajectory with maximal reward. Then the optimal steering angle with respect to the trajectory is determined by training an artificial neural network. Our method outperformed existing approaches and successfully found quality paths in various experimental settings, including the cases with obstacles.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.205-206
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• 2018

Recently, interest in unmanned vehicles, autonomous vehicles and connected cars has increased, and autonomous driving capability is also increasing. Depending on the autonomous driving ability, the maximum number of steps is divided into 6 steps. The higher the step, the less the involvement of the person in the running, and the person does not need to be involved at the highest stage. Today's autonomous vehicles have been developed in stages 4 to 5, but solutions are not clearly defined in case of an accident, so only the test run is possible. Such an accident occurring during traveling is almost inevitable, and it is judged who has made a mistake in case of an accident, which increases the punishment for the accident. Although a black box is used to clarify such a part, it is easy to delete a photographed image, and it is difficult to solve an accident such as a hit-and-run. In this paper, we design a driving record system using black chain to solve such an accident.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.916-921
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• 2018

Recently, interest in autonomous vehicle has increased, and autonomous driving capability is also increasing. Depending on the autonomous driving ability, the maximum number of steps is divided into 6 steps. The higher the step, the less the involvement of the person in the running, and the person does not need to be involved at the highest stage. Today's autonomous vehicles have been developed high level, but solutions are not clearly defined in case of an accident, so only the test run is possible. Such an accident occurring during traveling is almost inevitable, and it is judged who has made a mistake in case of an accident, which increases the punishment for the accident. Although a black box is used to clarify such a part, it is easy to delete a record, and it is difficult to solve an accident such as a hit-and-run. In this paper, i design a driving record system using black chain to solve accidents.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.621-622
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• 2019

본 논문은 도심 환경하에서 운행 가능한 자율주행차량 시스템의 구현 방안에 대해 다루고 있다. 현대자동차가 주최한 2019 대학생 자율주행 경진대회는 도심 환경을 재현한 K-City 에서 열렸고, 도심 환경에서 발생할 수 있는 돌발 장애물 인지, 공사 구간 우회, 교차로 신호등 인지, 사고 차량 회피, 응급 차량에게 차선 양보 및 톨게이트 통과 등의 6 개의 미션을 자율주행차량이 무인운전으로 수행하는 것이었다. 이 대회를 위해 본 연구팀에서 개발한 자율주행 시스템은 리웍된 실제 차량에 탑재되어 대회장의 모든 주행 미션을 성공적으로 수행하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.755-760
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• 2011

This paper presents a method for improving the positioning accuracy of the laser navigation. As a wireless navigation system, the laser navigation which is more flexible than a wired guidance system is used for the localization and control of an AGV(automatic guided vehicle). However, the laser navigation causes the large positioning error while the AGV turns or moves fast. To solve the problem, we propose the method for improving the positioning accuracy of the laser navigation using particle filter which has robust and reliable performance in non-linear/non-gaussian systems. For the experiment, we use the actual fork-type AGV. The AGV has a gyro, two encoders and a laser navigation. To verify the performance, the proposed method is compared with the laser navigation which is a product. In the experimental result, we verified that the proposed method could improve the positioning accuracy by approximately 66.5%.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.430-435
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• 2011

In this paper, a navigation technology of an unmanned vehicle using relative localization and magnetic guidance is proposed. Magnetic guidance system had been developed as a robust autonomous driving technology as long as magnetic fields on the path are detected. Otherwise, if magnetic fields were not detected due to some reasons, the vehicle could not drive. Therefore, in order to overcome the drawback, we propose that relative localization would be combined to magnetic guidance system. To validate the usefulness of the proposed method, a robotic vehicle was set up with the magnetic guidance system and the relative localization. In addition, the unmanned driving test was realized on the road without the magnetic fields so that the proposed method is verified by the experiment.