Bayesian-networks-based motion estimation for a highly-safe intelligent vehicle

Nguyen Van Dan, Michitaka Kameyama

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

Motion estimation of a moving object is one of the most important technologies to develop a next-generation highly-safe intelligent vehicle. Although intention of a driver in a target vehicle is key information for the motion estimation, we can not observe directly from sensors. This article presents a building method of Bayesian Networks (BNs) for motion estimation related to a driver's intention. Driver's intentions are hierarchically defined, so that the BN becomes as simple as possible. Causal relation between the intentions is discussed to reflect the real-world motion process. As a result, not only the quality of motion estimation but also the inference performance can be increased, Experimental learning system based on two-dimensional image processing is also presented for automatic acquisition of the BN probabilistic parameters.

本文言語English
ホスト出版物のタイトル2006 SICE-ICASE International Joint Conference
ページ6023-6026
ページ数4
DOI
出版ステータスPublished - 2006
イベント2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
継続期間: 2006 10 182006 10 21

出版物シリーズ

名前2006 SICE-ICASE International Joint Conference

Other

Other2006 SICE-ICASE International Joint Conference
CountryKorea, Republic of
CityBusan
Period06/10/1806/10/21

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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