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JACIII Vol.20 No.5 pp. 836-844
doi: 10.20965/jaciii.2016.p0836
(2016)

Paper:

Utterance Generation Based on Driving Evaluation for Driving Assistance Robot

Yoshikazu Okajima*, Hiroyuki Masuta*, Masatoshi Okumura*, Tatsuo Motoyoshi*, Ken’ichi Koyanagi*, Toru Oshima*, and Eiichi Takayama**

*Toyama Prefectural University
5180 Kurokawa Imizu-shi, Toyama 939-0398, Japan

**TAKAYAMA CARS., Co. Ltd.
3-36-6 Nakaizumi Komae-shi Tokyo 201-0012, Japan

Received:
February 22, 2016
Accepted:
August 1, 2016
Published:
September 20, 2016
Keywords:
communication robot, fuzzy inference, spiking neural network, ultra-compact electric vehicle
Abstract

This manuscript describes a robot interaction for the driving assistance system of an Ultra-Compact Electric Vehicle (UCEV). Fun-to-drive and safety are important for improving the commercial value of UCEV. To improve fun-to-drive and safety, the improvement of the driving skills is important. However, the driving assistance system of an ordinary vehicle only considers the objective driving evaluation. Therefore, we propose an interactive driving assistance system that considers the relation between the subjective as well as the objective driving evaluation. Furthermore, we install a communicating robot within a UCEV to interact with human beings in real time. As a first step, we propose a driving evaluation system by applying a simplified fuzzy inference, and an interaction timing estimation method by applying a spiking neural network. Through an off-line simulation experiment, we verify the effectiveness of our proposal that is able to generate a robot utterances content as well as estimate reasonable timing.

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Last updated on Sep. 21, 2017