NDLI: A framework of fault detection algorithm for intelligent vehicle by using real experimental data

Content Provider	IEEE Xplore Digital Library
Author	Hashimoto, N. Ozguner, U. Sawant, N. Yokozuka, M. Kato, S. Matsumoto, O. Tsugawa, S.
Copyright Year	2011
Description	Author affiliation: Meijo University, Japan (Tsugawa, S.) \|\| Department of Electrical Computer Engineering of the Ohio State University, Ohio, United States (Ozguner, U.) \|\| National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan (Hashimoto, N.; Yokozuka, M.; Kato, S.; Matsumoto, O.) \|\| Ohio State University, Ohio, United States (Sawant, N.)
Abstract	Automated vehicles have a possibility to contribute more capacity, safety, low emission and high efficiency to transportation. However, unstable conditions of the automated system can cause serious problem, thus the automated vehicle requires high reliability. The objective of this research is to develop algorithms of fault (unstable condition) detection for automated vehicles, and to improve the overall reliability of the system. In this study, we initially solved and updated identification of some pattern of data constellations under normal and unstable conditions through the experiments in a real world. The multiple experiments were done in the public area (course distance is about 1.1[km]) with some times, where some pedestrian, bicycles and other robots coexisted. The method of detecting faults utilizes mahalanobis distance, correlation coefficient and linearization in order to improve the reliability of detecting the faults correctly, because real experimental conditions include some random noises, and the method must be robust for the changing conditions. The feature of this study is to utilize the experiment results in real world, construct the algorithms and evaluate it. The simulations were done with the real experimental data, in order to evaluate it. The simulation result shows that the proposed system detects faults correctly, and it proves the validity of the proposed method proved.
Starting Page	913
Ending Page	918
File Size	303993
Page Count	6
File Format	PDF
ISBN	9781457721984
ISSN	21530009
e-ISBN	9781457721977
DOI	10.1109/ITSC.2011.6082877
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensors Mobile robots Fault detection Vehicles Mathematical model Equations
Content Type	Text
Resource Type	Article

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