Risk Estimation Method with Lambda Fuzzy Measure For Safety Driving Applications

Naoyori TANZAWA; Yutaka HATAKEYAMA; Kaoru HIROTA; Hiroshi TAKAHASHI

doi:10.14864/softscis.2006.0.1414.0

SCIS & ISIS 2006

セッションID: FR-G4-2

DOI https://doi.org/10.14864/softscis.2006.0.1414.0

会議情報

主催: Japan SOciety for Fuzzy Theory and intelligent informatics

共催: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

FR-G4 Fuzzy Measures and Cooperative Games

Risk Estimation Method with Lambda Fuzzy Measure For Safety Driving Applications

Naoyori TANZAWA, Yutaka HATAKEYAMA, Kaoru HIROTA, *Hiroshi TAKAHASHI

著者情報

キーワード: lambda-fuzzy measure, Fuzzy integral, Intelligent Driving Asistance

会議録・要旨集フリー

詳細

抄録

An accident risk estimation method based on traffic accident data using lambda-fuzzy measure reasoning is proposed for driving safety. This method contains knowledge about the traffic situation is inferred from traffic accident data using a lambda-fuzzy measure. Experimental results confirm that the proposed method is able to predict whether an accident will happen or not, and properly estimate the risk level of the traffic situation in advance, in the same manner as expert drivers. It is applied to the assessment of the risk level in actual driving situations, and designed for implementation in driver assistant systems.

責任著者(Corresponding author)

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