지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers 한국정보과학회 학술발표논문집 한국정보과학회 2011가을 학술발표논문집 제38권 제2호(B)
- 발행연도
- 2011.11
- 수록면
- 323 - 326 (4page)
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초록· 키워드
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This is an attempt towards building a probabilistic model of human driving behavior using hidden Markov models (HMMs) with continuous observations. After collecting needed driving data during a simulated driving task, the proposed segmentation and clustering algorithms are applied to group similar segments into nine different clusters. For each cluster one HMM is trained in a way to have maximum likelihood measure. In recognition phase, a sliding window of an unknown driving data is fed into each HMM, and the one with highest likelihood measure is marked as chosen cluster. The experimental results confirm the efficacy of the proposed approach by revealing recognition accuracy exceeding 85%.
목차
ABSTRACT
1. INTRODUCTION
2. PREVIOUS WORK
3. SYSTEM OVERVIEW
4. RESULTS
5. CONCLUSION and FUTURE WORK
6. ACKNOWLEDGEMENT
7. REFERENCES
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