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자율주행자동차의 추돌 회피를 위한 교통사고분석 및 기계 학습 기반 위험 시나리오 생성 연구
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Publication Year
2020-11
Journal
한국자동차공학회 논문집
Publisher
한국자동차공학회
Citation
한국자동차공학회 논문집, Vol.28 No.11, pp.817-826
Keyword
충돌 시나리오충돌 회피기능 안전검증기계 학습Collision scenarioCollision avoidanceFunctional safetyValidationMachine learning
Abstract
In this paper, the critical scenario generation method for the scenario-based approach is proposed to validate collision avoidance systems on autonomous vehicles. Along with three abstraction levels of scenarios for the safety of the intended functionality(SOTIF), as proposed by a PEGASUS project in Germany, critical scenarios based on fatal traffic accidents in Korea were analyzed statistically. Then, the collision scenario model, including all critical scenarios, is proposed to generate logical scenarios systematically. Since the high dimension of parameters in a logical scenario results in a combinatorial explosion of concrete scenarios, it is quite necessary to search for appropriate scenarios. Therefore, many safe scenarios were omitted by applying for a series of conditions based on time-to-collision and support vector machines. Finally, It is shown how scenarios can be generated to validate an automatic emergency braking system, and the critical scenarios are searched out via the proposed generation procedure.
ISSN
1225-6382
Language
Kor
URI
https://aurora.ajou.ac.kr/handle/2018.oak/37472
https://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART002639511
Type
Article
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SONG, BONGSOB송봉섭
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