Autonomous driving control for ITS by using learning automaton network with multiple environments

In this paper, the application of the learning automaton (LA) network with multiple environments is proposed for the adaptive controller for ITS autonomous driving. The LA network, which we introduced previously, has the ability to learn which deals with both multiple reinforcement signals and infor...

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Bibliographic Details
Published in:Electrical engineering in Japan 2005-03, Vol.150 (4), p.36-43
Main Authors: Shiraishi, Kazuaki, Hamagami, Tomoki, Koakutsu, Seiichi, Hirata, Hironori
Format: Article
Language:English
Subjects:
AHS
ITS
learning automaton
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Summary:In this paper, the application of the learning automaton (LA) network with multiple environments is proposed for the adaptive controller for ITS autonomous driving. The LA network, which we introduced previously, has the ability to learn which deals with both multiple reinforcement signals and information of multiple environments at the same time. This feature is found to be useful for improving the response of adaptation in dynamic environments such as highways. In order to evaluate the practical advantage of using the network, we designed a simulational highway system, constructed an autonomous travel controller using the simple LA and the LA network, and executed comparative experiments evaluating the performance of adaptation response and collision avoidance. The results show that the performance of the LA network with multiple environments is superior to that using simple LA application with regard to stability and safety. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 150(4): 36–43, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.10363
ISSN:0424-7760
1520-6416
DOI:10.1002/eej.10363