Intelligent Control Method and Self-position-azimuth Correction Method for Autonomous Vehicle

DOI

10.2991/jimet-15.2015.121How to use a DOI?

Keywords

Autonomous vehicle, Fuzzy-neural network, Self-position identification

Abstract

This paper proposes an intelligent control system using fuzzy-neural network (FNN) for autonomous vehicle .The autonomous vehicle will appropriately and automatically recognize and judge the running environment and run along a given orbit by using FNN. In order to acquire the training data of FNN, the driving knowledge is extracted from the human driving data. Then, the driving data is processed and normalized by rough set and defuzzy method. Moreover, a self-position-azimuth method is proposed to detect and correct the position and azimuth of the vehicle by outside-world information from stereo camera and laser sensor. The effectivity of the methods has been verified by tests using a model vehicle.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Takuya Nishimura
AU  - Sho Asai
AU  - Liuyang Song
AU  - Peng Chen
PY  - 2015/12
DA  - 2015/12
TI  - Intelligent Control Method and Self-position-azimuth Correction Method for Autonomous Vehicle
BT  - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference
PB  - Atlantis Press
SP  - 648
EP  - 655
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimet-15.2015.121
DO  - 10.2991/jimet-15.2015.121
ID  - Nishimura2015/12
ER  -