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Identification of Human Operations Using Data Clustering and its Applications to Automation
Author(s) -
Zanma Tadanao,
Sato Hayato,
Okada Tomomi,
Ishida Muneaki
Publication year - 2010
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20577
Subject(s) - cluster analysis , identification (biology) , task (project management) , automation , computer science , data mining , artificial intelligence , engineering , systems engineering , mechanical engineering , botany , biology
Some human operations are realized by the combination of continuous behaviors and logical judgment. Such a system is called a hybrid dynamical system (HDS). In this study, we consider a driving task as an HDS. Then, we identify the task using the clustering method, which is one of the methods used to identify an HDS. In addition, we apply the identified model to an automatic driving system. Both the simulation and application results illustrate the effectiveness of the proposed approach. © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.