Vehicle Control Based on Fuzzy Evaluation Knowledge Obtained by Coefficients of the ARMA Model | Zendy

Hiroshi Takahashi | Zendy

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Vehicle Control Based on Fuzzy Evaluation Knowledge Obtained by Coefficients of the ARMA Model

Author(s) -

Hiroshi Takahashi

Publication year - 1997

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.1997.p0008

Subject(s) - computer science , headway , fuzzy logic , task (project management) , control (management) , fuzzy control system , autoregressive–moving average model , intelligent transportation system , autoregressive model , artificial intelligence , simulation , machine learning , mathematics , engineering , civil engineering , systems engineering , econometrics

This paper presents a study on an intelligent vehicle that uses the driver's subjective evaluation model. The subject's driving task is to follow the car in front of him (the first car) and to keep the headway distance between the two cars consistent. Using ARMA model and fuzzy logic I created a subjective evaluation model that can predict the driver's subjective evaluation while performing this driving task. I realized that a subjective evaluation feedback control system would be very useful in future vehicles.

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