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채흥석,정용환,이명수,신재곤,이경수,Chae, Heungseok,Jeong, Yonghwan,Lee, Myungsu,Shin, Jaekon,Yi, Kyongsu 한국자동차안전학회 2017 자동차안전학회지 Vol.9 No.1
Regulation for the testing and operation of automated vehicles on public roadways has been recently developed all over the world. For example, the licensing standards and the evaluation technology for automated vehicles have been proposed in California, Nevada and EU. But specific safety evaluation scenarios for automated vehicles have not been proposed yet. This paper presents safety evaluation scenarios for extraordinary service permission of automated vehicles on highways. A total of seven scenarios are selected in consideration of safety priority and real traffic situation. Six scenarios are relevant with lane keeping and one scenario is relevant with lane change. All scenarios are developed based on existing ADAS evaluation scenarios and repeated simulation of automated vehicle algorithm. Safety evaluation factors as well as scenarios are developed. The safety factors are based on existing ADAS ISO requirements, ADAS safety factors and current traffic regulations. For the scenarios, a hunter vehicle is needed in addition to automated vehicle evaluated. The hunter vehicle performs multiple roles like preceding vehicle, cut-in vehicle and so on. The hunter vehicle is also automated vehicle equipped with high performance GPS, radar and Lidar. All the scenarios can be implemented by driving a lap on a KATRI ITS test track. These scenarios and safety evaluation factors are investigated via both a computer simulation and an experimental vehicle test on the test track. The experimental vehicle test was conducted with two automated vehicles, which are the evaluated vehicle and the hunter vehicle.
박종철,채흥석,이경수,Park, Jongcherl,Chae, Heungseok,Yi, Kyongsu 한국자동차안전학회 2018 자동차안전학회지 Vol.10 No.1
This paper presents an analysis on driving safety in lane change situation based on road driving data. Autonomous driving is a global trend in vehicle industry. LKAS technologies are already applied in commercial vehicle and researches about lane change maneuver have been actively studied. In autonomous vehicle, not only safety control issue but also imitating human driving maneuver is important. Driving data analysis in lane change situation has been usually dealt with ego vehicle information such as longitudinal acceleration, yaw rate, and steering angle. For this reason, developing safety index according to surrounding vehicle information based on human driving data is needed. In this research, driving data is collected from perception module using LIDAR, radar and RT-GPS sensors. By analyzing human driving pattern in lane change maneuver, safety index that considers both ego vehicle and surrounding vehicle state by using relative velocity and longitudinal clearance has been designed.
자율주행을 위한 레이더 기반 인지 알고리즘의 정량적 분석
이호준,채흥석,서호태,이경수,Lee, Hojoon,Chae, HeungSeok,Seo, Hotae,Yi, Kyongsu 한국자동차안전학회 2018 자동차안전학회지 Vol.10 No.2
This paper presents a quantitative evaluation method and result of moving vehicle perception using automotive radar. It is also important to analyze the accuracy of the perception algorithm quantitatively as well as to accurately percept nearby moving vehicles for safe and efficient autonomous driving. In this study, accuracy of the automotive radar-based perception algorithm which is developed based on interacting multiple model (IMM) has been verified via vehicle tests on real roads. In order to obtain experimental data for quantitative evaluation, Long Range Radar (LRR) has been mounted on the front of the ego vehicle and Short Range Radar (SRR) has been mounted on the rear side of both sides. RT-range has been installed on the ego vehicle and the target vehicle to simultaneously collect reference data on the states of the two vehicles. The experimental data is acquired in various relative positions and velocity, and the accuracy of the algorithm has been analyzed according to relative position and velocity. Quantitative analysis is conducted on relative position, relative heading angle, absolute velocity, and yaw rate of each vehicle.
주행데이터 기반 자율주행 안전성 평가 시나리오 개발 및 검증
임형호,채흥석,이명수,이경수,Lim, Hyeongho,Chae, Heungseok,Lee, Myungsu,Lee, Kyongsu 한국자동차안전학회 2017 자동차안전학회지 Vol.9 No.4
As automotive industry develops, the demand for increasing traffic safety is growing. Lots of researches about vehicle convenience and safety technology have been implemented. Now, the autonomous driving test is being conducted all over the world, and the autonomous driving regulations are also being developed. Autonomous vehicles are being commercialized, but autonomous vehicle safety has not been guaranteed yet. This paper presents scenarios that assess the safety of autonomous vehicles by identifying the minimum requirements to ensure safety for a variety of situations on highway. In assessing driving safety, seven scenarios were totally selected. Seven scenarios were related to lane keeping and lane change performance in certain situations. These scenarios were verified by analyzing the driving data acquired through actual vehicle driving. Data analysis was implemented via computer simulation. These scenarios are developed based on existing ADAS evaluation and simulation of autonomous vehicle algorithm. Also Safety evaluation factors are developed based on ISO requirements, other papers and the current traffic regulations.
최현재(HyunJae Choi),채흥석(HeungSeok Chae) 한국정보과학회 2016 정보과학회논문지 Vol.43 No.4
탐색 기반 테스팅은 넓은 탐색 범위에서 효과적으로 테스트 데이터를 생성하는 대표적인 기술중 하나이다. 탐색 기반 테스팅의 성능이 프로그램의 구조적 특성에 영향을 받는 것이 알려져 있음에도 구조적 특성을 고려한 탐색 기반 테스팅 비교 연구는 제한적으로 수행되었다. 본 연구는 탐색 기반 테스팅 비교를 통해 테스트 대상의 구조적 특성 차이에 따른 최적 알고리즘을 분석하고자 한다. 실험 결과의 일반화를 위해 탐색 성능에 영향을 주는 4가지 메트릭 값을 조합하여 19,800개의 테스트 대상 프로그램을 자동 생성하였다. 실험 결과 복잡도가 높은 프로그램을 20,000번 이하의 횟수로 분석하였을 경우에는 유전알고리즘이 가장 우수한 성능을 보였으나 50,000번 이상 분석하였을 경우에는 유전 담금질 기법과 담금질 기법이 다른 알고리즘들 보다 우수한 성능을 보였다. 복잡도가 낮은 프로그램에서는 유전 담금질 기법, 담금질 기법, 언덕 오르기 방법이 다른 알고리즘들 보다 우수한 성능을 보였다. Search-Based Software Testing (SBST) is an effective technique for test data generation on large domain size. Although the performance of SBST seems to be affected by the structural characteristics of Software Under Test (SUT), studies for the comparison of SBST techniques considering structural characteristics are rare. In addition to the comparison study for SBST, we analyzed the best algorithm with different structural characteristics of SUT. For the generalization of experimental results, we automatically generated 19,800 SUTs by combining four metrics, which are expected to affect the performance of SBST. According to the experiment results, Genetic algorithm showed the best performance for SUTs with high complexity and test data evaluation with count ≤ 20,000. On the other hand, the genetic simulated annealing and the simulated annealing showed relatively better performance for SUTs with high complexity and test data evaluation with count ≥ 50,000. Genetic simulated annealing, simulated annealing and hill climbing showed better performance for SUTs with low complexity.
RFID 미들웨어 시스템에 적합한 성능 장애 진단 기법 연구
임종호(Jongho Lim),채흥석(Heungseok Chae) 한국정보과학회 2007 한국정보과학회 학술발표논문집 Vol.34 No.2B
RFID(Radio Frequency Identification) 시스템은 다양한 분야에서 혁신을 제공하는 기술로써 관심의 대상이 되고 있으며 여러 분야에서 RFID 기술을 도입하기 위해 연구되고 있다. 특히 많은 사업 분야에서 RFID 기술을 이용하기 위해 연구가 이루어지고 있다. RFID 시스템의 특성상 다양한 도메인에서 이용되기 때문에 여러 가지 장애가 발생하게 된다. 하지만 이렇게 발생한 다양한 장애들을 탐지하고 진단하는 일은 쉽지 않다. 본 논문에서는 다양한 도메인에서 이용되는 RFID 미들웨어 시스템의 특성을 고려하여 RFID 미들웨어 시스템에 적합한 장애 탐지 기법과 장애 진단 기법을 제시한다.
전동식 조향 장치의 성능 평가를 위한 신경 근육계 기반 운전자 모델 개발
이성현,이동필,이재풍,채흥석,이명수,이경수,Lee, Sunghyun,Lee, Dongpil,Lee, Jaepoong,Chae, Heungseok,Lee, Myungsu,Yi, Kyongsu 한국자동차안전학회 2017 자동차안전학회지 Vol.9 No.3
This paper presents a lateral driver model with neuromuscular system to evaluate the performance of electric power steering (EPS). Output of most previously developed driver models is steering angle. However, in order to evaluate EPS system, driver model which results in steering torque output is needed. The proposed lateral driver model mainly consists of 2 parts: desired steering angle calculation and conversion of steering angle into steering torque. Desired steering angle calculation part results in steering angle to track desired yaw rate for path tracking. Conversion of steering angle into torque is consideration with neuromuscular system. The proposed driver model is investigated via actual driving data. Compared to other algorithms, the proposed algorithm shows similar pattern of steering angle with human driver. The proposed driver can be utilized to efficiently evaluate EPS system in simulation level.