• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.53-59
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• 2022

After the 3rd level autonomous driving vehicle, the 4th and 5th level of autonomous driving technology is trying to maintain the optimal condition of the passengers as well as the perfect driving of the vehicle. However current autonomous driving technology is too dependent on visual information such as LiDAR and front camera, so it is difficult to fully autonomously drive on roads other than designated roads. Therefore this paper proposes a Braking Strength Calculation System (BSCS), in which a vehicle classifies road conditions using data other than visual information and calculates optimal braking strength according to road conditions and driving conditions. The BSCS consists of RCDM (Road Condition Definition Module), which classifies road conditions based on KNN algorithm, and BSCM (Braking Strength Calculation Module), which calculates optimal braking strength while driving based on current driving conditions and road conditions. As a result of the experiment in this paper, it was possible to find the most suitable number of Ks for the KNN algorithm, and it was proved that the RCDM proposed in this paper is more accurate than the unsupervised K-means algorithm. By using not only visual information but also vibration data applied to the suspension, the BSCS of the paper can make the braking of autonomous vehicles smoother in various environments where visual information is limited.

• Journal of Biosystems Engineering
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• v.21 no.4
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• pp.422-428
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• 1996

This study was conducted to developed to develop a simple battery-powered autonomous vehicle for greenhouse works. A steering method using speed difference of two independent driving motors was adopted. DC motor driving circuit, speed control circuit and controller using one-chip microcomputer were constructed. The inputs of controller are rolling of the vehicle and current speed of driving motors. Using these signals, automatic guidance system along furrow was developed. A computer simulation program by the kenematic analysis was developed to find out optimal control algorithm. The results of this study are as follows. 1. Automatic guidance system along the furrow that adopted two independent driving motors and rolling of vehicle was developed. 2. The results of simulation showed that PID control was adequate to automatic guidance system along furrow. 3. Two commercial 12V battery serially connected were able to drive the vehicle on the soil ground for five hours in continuous operation and for four hours in intermittent operation without recharging the battery. 4. The speed range was 0-0.7m/s and the rolling of vehicle could be controlled within $pm5^{\circ}$ range. 5. From a series of tests, developed vehicle was found to be a useful tool for greenhouse works.

• Journal of Auto-vehicle Safety Association
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• v.15 no.4
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• pp.88-94
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• 2023

The seating postures of passengers in the automated driving vehicle are possible in atypical forms such as rear-facing and lying down. It is necessary to improve devices such as airbags and seat belts to protect occupants from injury in accidents of the automated driving vehicle, and collision safety evaluation tests must be newly developed. The purpose of this study is to define representative types of head-on collision accidents to develop collision standards for autonomous vehicles that take into account changes in driving behavior and occupants' postures. 150 frontal collision cases remained by filtering (accident videos, images, AIS 2+, passenger car, etc…) and random sampling from approximately 320,000 accidents claimed by a major insurance company over the past 5 years. The most frequent accident type is a head-on collision between a vehicle going straight and a vehicle turning left from the opposite side, accounting for 54.7% of all accidents, and most of these accidents occur in permissive left turns. The next most common frontal collision is the center-lane violation by drowsy driving and careless driving, accounting for 21.3% of the total. For the two types above, data such as vehicle speed, contact point/area, and PDOF at the moment of impact are obtained through accident reconstruction using PC-Crash. As a result, two types of autonomous vehicle crash safety test scenarios are proposed: (1) a frontal oblique collision test based on the accident types between a straight vehicle and a left-turning vehicle, and (2) a small overlap collision test based on the head-on accidents of center-lane violation.

• Convergence Security Journal
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• v.18 no.4
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• pp.53-61
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• 2018

Recently 4th Industrial Revolution era has come up and autonomous vehicle gets a huge attention for its commercialization as well as development. To this end, many countries such as US, UK, Germany are looking into laws and policies related to autonomous vehicle making a new law system, laws, policies or at least modifying the existing ones. Korea is also facing commercialization and development of autonomous vehicle yet it's law system, laws and policies are far beyond comparing to those of advanced countries. This paper details current law system comparison of several countries providing differences and characteristics for the purpose of success of auto drive vehicle industry. On top of that we suggest a new law system, laws and policies and then provide directions as steps for mature implementation. In addition, we discuss how the new laws and policies can bring out successful commercialization as well as industrial success of autonomous vehicle at the points of consumers, vehicle makers, insurance companies, and government.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.50-58
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• 2015

The research on autonomous vehicle that expected to greatly reduce accidents by driver's mistakes is increasing in the development of technology. The purpose of this research is to identify the factor that affect trust in autonomous vehicles and analyze the requirements of the driver in autonomous vehicles environment. Therefore, in this study, we defined the information and functions provided by the autonomous vehicles through the investigation of the prior studies, conducted a questionnaire survey and focused group interview (FGI). The results show that competency, error management were important factors influencing trust in autonomous vehicles and identified that driver took safety related information as high priority in autonomous vehicle. Also, it was identified that driver prefer to perform the multimedia function in autonomous vehicle environment. The study is looking forward to be the reference data for design of advanced autonomous vehicle. It will contribute to the improvement of the convenience and satisfaction of the drivers.

• Journal of Auto-vehicle Safety Association
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• v.15 no.3
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• pp.53-58
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• 2023

Defects in the vehicle itself were considered the biggest risk factor for traffic accidents as the electrical and electronic components of vehicles, which were not there before, increase. Therefore, the vehicles have been developed based on ISO 26262 (an international functional safety standard) which is focusing on functional defect safety evaluation of electrical and electronic component systems. However, in the future, as autonomous driving technology is applied, even vehicles without functional defects must be prepared for the dangerous traffic situation that may arise from exceptional or external factors. SOTIF (Safety Of The Intended Functionality) is a concept to prevent exceptional or external factors. The main objective of SOTIF is to decrease Unknown & Unsafe factors as much as possible by finding Known factors and Unsafe factors. In this study, Prescan provided SIEMENS, one of the autonomous driving simulators, is used to make scenarios of IGLAD traffic accident cases. From the simulation results, Unsafe & Safe cases were classified and analyzed to derive unsafe factors.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.198-208
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• 2022

In this paper, an autonomous driving system is implemented for the Segye AI Robot Race Competition that multiple vehicles drive simultaneously. By utilizing the ERP42-racing platform, RTK-GPS, and LiDAR sensors provided in the competition, we propose an autonomous driving system that can drive safely and quickly in a road environment with multiple vehicles. This system consists of a recognition, judgement, and control parts. In the recognition stage, vehicle localization and obstacle detection through waypoint-based LiDAR ROI were performed. In the judgement stage, target velocity setting and obstacle avoidance judgement are determined in consideration of the straight/curved section and the distance between the vehicle and the neighboring vehicle. In the control stage, adaptive cruise longitudinal velocity control based on safe distance and lateral velocity control based on pure-pursuit are performed. To overcome the limited experimental environment, simulation and partial actual experiments were conducted together to develop and verify the proposed algorithms. After that, we participated in the Segye AI Robot Race Competition and performed autonomous driving racing with verified algorithms.

• Journal of Auto-vehicle Safety Association
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• v.14 no.3
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• pp.6-16
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• 2022

Recent, the issue of the fourth industrial revolution triggered by technological advances has changed the automobile industry centered on internal combustion engines, and quantitative growth of the global automobile market, which has grown rapidly, has been slowing since 2015. These advances in technology are expected to develop beyond the advanced driver assistance system to autonomous driving technology. According to SAE-J3016 published by the Society of Automotive Engineers, the technology of autonomous vehicles is divided into a total of six stages according to the driver's intervention and automation level from 0 to 5. Securing safety for autonomous vehicles is important. But, research on safety evaluation theory and autonomous vehicle evaluation method based on real vehicle test is insufficient. In this study, the longitudinal distance theory equation and continuous test scenario were proposed for the test method of autonomous vehicles for fixed targets, and the real vehicle test was conducted. When comparing the theoretical values compared to the measured values, it was determined that it was reliable with a minimum error rate of 0.484% and a maximum error rate of 7.391%. Using the proposed theoretical equation, it is judged that it can be used as a safety evaluation method in an environment where real vehicle test is not possible because it can grasp the trend in the longitudinal direction in the development stage.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.162-170
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• 2022

Today, automobiles have become an indispensable element in people's lives, and the distribution of vehicles with various autonomous driving functions is expanding. Sensors such as cameras are used to recognize various situations on the road as an essential element for autonomous driving functions, but camera sensors have disadvantages that are vulnerable to bad weather. In this paper, we present a derivation process that defines external weather environment factors that negatively affect the performance of a camera for an autonomous vehicle. Through the proposed process, it is expected that it will contribute to securing the reliability of the camera and further improving the safety of autonomous vehicles.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.129-143
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• 2019

As the importance of autonomous vehicle safety is emphasized, the application of ISO-26262, a development verification guideline for improving safety and reliability, and the safety verification of autonomous vehicles are becoming increasingly important, in particular, SAE standard level 3 or higher level autonomous vehicles detect and decision the surrounding environment instead of the human driver. Therefore, if there is and failure or malfunction in the autonomous driving function, safety may be seriously affected. So autonomous vehicles, it is essential to apply and verity the safety concept against failure and malfunctions. In this study, we study the fault injection scenarios for safety evaluation and verification of autonomous vehicles using ISO-26262 part3 process and STPA were studied and safety measures for safety concept design were studied through simulation bases fault injection test.